The National Cancer Institute Real Time Picture Processor

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This history was compiled by Peter Lemkin with interviews, recollections, and content from Lewis Lipkin, George Carman, Bruce Shapiro, and Morton Shultz and some of the users (Carl Merril, Peter Sonderegger, Eric Lester). It could not have been done without everyone's input, which is reflected throughout the history. See the Acknowledgements for additional credits and information on online reference material donated as part of this history.

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Many properties of biological materials can be visualized directly using microscopy, electrophoresis, or other visualization mechanisms. The image subjects may have been improved before digital image capture using various detection-enhancement methods (such as stains, dyes, autoradiography, phase-contrast, interference microscopy, etc.) to visualize the data of interest. Digital image processing (see wikipedia.org Image Removed and  and dictionary.com Image Removed entries) is a method for the separation, detection, and quantification of the objects of interest in biological materials. Quantified data helps scientists perform more rigorous analyses of their biological experiments and improve the conclusions of their analyses.

There are two major goals of this history: to document the events and conditions that led to the creation of one of the first grayscale image processors, and to describe the highly effective complementary collaboration that allowed alloAsilomar Third Engineering Foundation Conference on Automated Cytologywed this project to flourish. Occasionally, references will be made to other later advances indirectly related to the RTPP work that would not have happened without the RTPP. Where possible, we have linked to open access journal PDFs, and have included PDFs of the key technical reports describing the RTPP on this Web site.

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The RTPP project was conceived and initiated by Dr. Lewis "Lew" Lipkin, M.D., head of the Image Processing Unit, later the Image Processing Section (IPS), in the the National Cancer Institute (NCI). The intellectual concept behind computer-controlled microscopy started in 1962 when Lew was an assistant professor of neuropathology at Downstate Medical Center in New York. Professor Patrick Fitzgerald, Chairman of the Pathology Department at Downstate, was studying pancreatic cell growth. Dr. Vinichaichol, who was doing visual grain counts on thin pancreatic sections, was finding mixed results. The problem was statistical. Dr. Lipkin was asked to design a proper sampling technique. Grain counting was  Grain counting was a method used to measure cell metabolism before the days of antibody techniques applied to living cells and fluorescent techniques that came about during our time in NIH. Lew, who happened to know something about statistics, was asked by Dr. Fitzgerald to find out what was wrong with his statistics. After some thought, Lew realized that Dr. Vinichaichol was staying in one area of the slide and he had no way of knowing when he was recounting the same cells. Lew didn't want to continue looking at biological material that he couldn't explore without using some form of quantification.

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Dr. Richard Masland, M.D., the director of the National Institute of Neurological Disease and Blindness (NINDB), invited Lew to join the National Institutes of Health (NIH) in 1962. Lew was one of perhaps 20 neuropathologists in the country at the time. Later NINDB became the National Institute of Neurological Disorders and Stroke (NINDS). NINDB was looking for a neuropathologist for the Perinatal Research Branch (PRB) headed by Dr. Heinz Berendes, M.D. When he first came to NIH, Lew was determined to build something that implemented his ideas of mapping in biological images. He had an original LINC (Laboratory INstrument Computer created at MIT with NIH funding) computer at the time. Later, Lew upgraded this to a Digital Equipment Corporation Image Removed (DEC) LINC-8 Image Removed. The problem: he had a microscope and he had a computer. How could he combine the two?

The first thing he wanted to be able to do was move a slide via a computer-controlled microscope stage. Initially, he was going to do it with analog feedback. He talked to Wes Clark (who had helped build the LINC computer with Charlie Molner and others). Wes convinced Lew that he really wanted a digital stage - not an analog one - so that is what Lew developed: a series of stepping-motor-controlled stages that improved with each generation. The original design connected the stage with rubber bands, which was then greatly improved with direct stepping-motor drives. Lew had also been working with Russell Kirsch and Bill Watt from the National Bureau of Standards (NBS, now the National Institute of Standards and Technology or NIST Image Removed). This early work involved describing biological images using computer picture grammars [1] that attempted to bring artificial intelligence and algorithmic methods to the description of biological images.

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The second computer-controlled microscope project was the NCI grain counter [2] that is discussed in its own section. Advancements in electronics technology enabled us to design the grain counter using high-speed shift-register memory chips to capture X,Y coordinates from a 10 frame/second non-interlaced TV system ( Imanco Imanco Quantimet 720 Image Removed). Despite these advances, for larger image memories such as was needed for the RTPP, it would have been very difficult to implement image processing algorithms. This is because shift-register memory has delays in accessing any particular image pixel datum since the data must cycle around the circular shift register before the computer could access it. For complex algorithms with millions or billions of operations, this would be intolerable.

The culmination of these efforts was the Real Time Picture Processor (RTPP) described in journal papers [3, 4, 5, 6], as well as technical reports to be discussed and listed at the end of this history. We started this project just as the new Texas Instruments 4K bits X 1-bit dynamic RAMs (Random Access Memory - see history ofDRAM Image Removed) became available. Their availability was discovered by George Carman who proceeded to design the RTPP using these new chips. Many skilled people made this project possible: the superb computer hardware architecture work by George and the mechanical engineering work by Sprague Hazard; the coming together of the right group of people, with synergistic skills who got along as a family, at the right time when the technology and the NIH's support resources were available; the NCI's Director Seymour Perry and administrator Bill Penland gave us crucial encouragement and financial support. Dr. Perry invited us to move to NCI as the Image Processing Unit (IPU) about 1972. In projects of this type, there is a window of time when the technology is appropriate for the job. Without the 4K dynamic RAMs, the RTPP would not have been possible. We were doing cutting-edge research, but a year or two later, charge-coupled devices would make their appearance and eventually make much of our design obsolete. But that is the nature of progress.

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One of the unique aspects of the RTPP was to implement the design as special-purpose parallel hardware with a flexible bus-architecture and a microcoded instruction set that reflected the types of operations routinely performed in image processing [3-4, TR-2, TR-7, TR-7a, TR-22]. Although other image processing computers were available, such as the ILLIAC-III Image Removed, using a microcode architecture enabled an image processor to be constructed and built less expensively but with greater flexibility than building it entirely with discrete hardware. The special-purpose hardware could make real-time results possible (defined as reasonably fast enough to incorporate human feedback in tuning algorithms, such as interactively adjusting detection thresholds, etc.). A National Technical Information Service (NTIS)technical report [TR-7] describing the RTPP was one of the frequently requested reports one month as reported in their monthly newsletter for November 1976 under computer topics.

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Scientists used the RTPP as finally constructed to analyze data in a variety of biomedical domains including optical microscope images of optical serial sections of brain tissue, stained bone marrow smears, and tissue cultures using phase contrast and differential interference optics. The latter was used in tracking cell membrane extents of macrophages in tissue culture over time as the cells tried to phagocytize various types of asbestos fibers. The goal was to better understand fiber carcinogenicity and the dynamics of fiber ingestion [8, 9, 10]. The bone marrow smear image analysis was part of my Ph.D. dissertation [11, 12, TR-653, TR-655]. The RTPP was also used for 2D electrophoretic gel images for a variety of biological materials [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32], and for RNA electron micrographs of secondary structure, which was part of Bruce Shapiro's Ph.D. dissertation [33, 34, 35, 36, 37, 38, TR-BAS78].

Image ModifiedFigure 1. Dr. Lewis Lipkin headed the project. His group started working on computer-controlled optical microscopy in the Perinatal Research Branch (PRB) of NINDB. The group later changed its name and institutes to the Image Processing Unit (IPU) in NCI in the Laboratory of Pathology. IPU later became the Image Processing Section (IPS) in NCI. The Section later became part of the Laboratory of Mathematical Biology (LMMB) in NCI under Dr. Charles DeLisi, Ph.D., and still later under Dr. Jacob Maizel, Ph.D.. The laboratory changed its name to the Laboratory of Experimental and Computational Biology (LECB) under Jake Maizel. The laboratory is currently refocused on nanobiology and is now called the Center for Computer Research Nanobiology Program (CCRNP) directed by Dr. Robert Blumenthal, Ph.D.(CCRNP has an additional research Web site).

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• Lewis Lipkin, M.D., (mathematics and physical chemistry, and a neuropathologist), Head of the Image Processing Section (IPS); previously the (PRB, NINDB) and then the Image Processing Unit (IPU) in the NCI.
• Peter Lemkin, Ph.D. & M.S. EE, computer scientist and electrical engineer, IPS/NCI, and previously in (PRB, NINDB) and in IPU/NCI
• George Carman, M.S. EE, electrical engineer and computer hardware architecture, Technical Development Section (TDS), NINDB; Carman Engineering (now Lucidyne Corp Image Removed).
• Morton Schultz, B.S. EE, electrical engineer, IPS/NCI, and previously in IPU/NCI
• Bruce Shapiro, Ph.D., B.S. math & physics, computer scientist, IPS/NCI, and previously in (PRB, NINDB),and in IPU/NCI
• Sprague Hazard, mechanical engineer (contractor consultant)
• Peter Kaiser, B.S. CS, computer scientist (IPU) in the NCI
• Earl Smith, M.S. CS, computer scientist (IPU) in the NCI
• Dan Kilgore, B.S. EE, computer programmer [Digital Equipment Corp Image RemovedCorp (DEC) software engineer]
• Tom Duval and later Jim Camper, electronics technicians - helped construct the RTPP racks, and power-supplies cabinets
• Cambion Corporation, wire-wrapped the remaining 63 buffer memory boards and the back-planes

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• Lewis Lipkin: optical microscopy of serial brain sections and macrophage motility measurements with asbestos
• Peter Lemkin: bone marrow smear analysis, 2D gel electrophoresis
• Bruce Shapiro: RNA secondary structure of electron micrograph
• Carl Merril: NIMH/NIH - 2-dimensional (2D) gel electrophoresis, E.coli mutants and macrophages with asbestos
• Jacob Maizel: NICHD/NIH, with Bruce Shapiro - RNA electron microscopy of secondary structure
• Eric Lester: NCI, U. Chicago, and oncology practice - 2D gel electrophoresis on human leukemia
• Steve Aley and Russell Howard: NIAID/NIH - 2D gel electrophoresis of Plasmodium knowlesi clones
• Peter Wirth and Snorri Thorgeirsson: NCI/NIH - 2D gel electrophoresis on liver cell lines
• Peter Sonderegger: NICHD/NIH and U. Zurich - 2D gel electrophoresis of axonal proteins of sensory and motor neurons

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Div class desktop:grid-col-6 Image Modified Div class desktop:grid-col-6 Figure 2. One of the first images taken using the RTPP was of the development group just after we got the Digital Equipment Corporation DECsystem-2020 interface to the RTPP buffer memory working. The image was one we called "mcrew" (i.e., 'machine crew'). Top row (L-R): Dan Kilgore, George Carman, and Morton Schultz. Bottom row (L-R): Earl Smith and Peter Lemkin. Not shown: Bruce Shapiro and Lew Lipkin who were integral parts of the RTPP design and development team.

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Div class desktop:grid-col-6 Image Modified Div class desktop:grid-col-6 Figure 3. The Digital Equipment Corporation DECsystem-2020 Image Removed running the TOPS-10 Image Removedoperating system. The system is shown with Bruce Shapiro, holding a removable 180MB "bathtub" size disk pack (on the left), and Peter Lemkin (on the right). It had 512K words, 36-bits/word, 256K word virtual space/user, a very powerful instruction set, and many high-level computer languages, including SAIL (Stanford Artificial Intelligence Language - see wikipedia.org entry on SAIL) Image Removed, that made implementing complex analysis algorithms much easier than on the PDP8e. SAIL was developed by Dan Swinehart and Bob Sproull of the Stanford AI Lab Image Removed in 1970. Sproull was at Division of Computer Research and Technology (DCRT) in the early 1970s and introduced the language to DCRT [the precursor of NIH's Center for Information Technology (CIT)]. Over time, we implemented more of the advanced image processing and pattern recognition algorithms in SAIL, using the RTPP as a sophisticated data acquisition and interactive graphics front-end. Later many of these algorithms were rewritten in C and UNIX using X-windows (we rewrote the C/UNIX/X-windows GELLAB-II Image Removed exploratory analysis system from the SAIL/TOPS-10/RTPP GELLAB-I), and in LISP (StructureLab with a Symbolics Lisp machine and later a Unix Platform) when the DECsystem-10/20 computer lines were phased out in favor of the VAX Image Removedcomputer lines. Later still, much of the C code for GELLAB-II was converted and rewritten in Java and used as part of the Open2Dprot Image Removed project. We will discuss some of these projects later under the section Applications of the RTPP in Biomedical Research.

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The design of the RTPP was presented at the 1973 Asilomar Third Engineering Foundation Conference on Automated Cytology Image Removed and published in 1974 [3-4]. This conference and a subsequent automated cytology workshop concentrated on the two solutions then available: image processing and pattern recognition of cell images, and the evolving field of flow cytometry. NIH was funding both fields. During this time we developed plans for integrating artificial intelligence techniques for understanding and analyzing biological materials and systems incorporating the RTPP, and these were also presented at the Asilomar workshop [5, TR-15].

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Not only did Cambion build the buffer memory boards, but using their standard technology, they also wired much of the backplanes. Their technology was an integrated system, and had been developed for rapid prototype construction in aerospace projects. It included cards, sockets, and racks. The system would not have worked had the parts been obtained from different vendors. By adapting Cambion's standards, we were able to take advantage of the reliability Cambion had developed for this kind of work. After Cambion created the boards and backplanes, our electronics technicians assembled them into several cabinets of 19" vertical racks including one cabinet for the power supplies. The buffer memories were 16 cards to a rack, with four racks. To avoid overheating, the cards were inserted in every other slot. Then the equipment was shipped to George in Oregon to finish construction and debugging. We had purchased a PDP8e for him to use in developing, debugging, and testing the interface. The computer was also critical for George to create various software tools to help manage the project. These included a wirewrap database program that could take pairs of (drawing #, chip #, pin #) triples that indicated a pair of wires to be connected using a technique called "wirewrap." This methodology was critical since a single buffer memory card was described in a large number of blueprints and it would be difficult to keep straight which pins connected to other pins in this complex global diagram. George then wrote additional software to translate these pairs to the standard lists that Cambion required. In a biomedical image processing and electronics conference, George's triple notation and his new way to handle the increasing complexity of multiple drawing wiring lists received a good reception from some of the developers of VHDL Image Removed (a hardware description language). Because of space limitations, George put the PDP8e into a closet of his house with additional AC cooling. The PDP8e at that time cost more than his house. Today, the most inexpensive computers are many orders of magnitude more powerful than the PDP8e at a small fraction of their cost.

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The Axiomat was a dream microscope. (A photograph Image Removed is available on Zeiss's microscope history Web page.) The microscope complex grew in the sense that as we wanted more and more control of the microscope functionality, we added it. In addition to control of the stage and control of the Z-axis, we also wanted control of the frequency of light that went through it. Although we experimented with various color selection methods, we settled for using interference filters. The RTPP and the microscope were controlled in real-time by a polling routine in BMON2 with the (X,Y,Z) direction control switches, A/Ds, and other states available for programs needing this data. Of course Lew Lipkin's pick-list idea was implemented and was part of BMON2.

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The software control program for the buffer memory I constructed on the PDP8e was called BMON2 (the Buffer Memory Monitor System) [40, TR-21, TR-21b, TR-23] and written in Fortran-II. BMON2, in addition to interfacing with the RTPP, also allowed running other programs to be batched to analyze the data. Given that the PDP8e had 32K words of memory, this was critical for doing complex sequential operations and for easily writing new RTPP applications. A Fortran-II library that could interface with the RTPP, BMOMNI [TR-23], allowed these other programs to access the RTPP as required. (See discussion on Fortran-II in the section on the grain counter. This shows the BMOMNI Fortran code.) BMON2 could capture and display images and do many image processing operations on the PDP8e. Another program called FLICKER [13] ran on the PDP8e and was used to analyze 2D gel images visually by alternately displaying one movable image on the video screen relative to another that was held in a constant screen position. Later, it allowed the comparison of two saved images as well. So a set of images could be compared against a reference sample. Some of the ideas on using flickering images to detect subtle differences in image matching were suggested by Bernice Lipkin, who is an expert in psychopictorics [41]. A third-generation version of FLICKER is available as open-source software at http://open2dprot.sourceforge.net/Flicker Image Removed.

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Fortran-II source code of BMON2 and the image processing functions

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A Digital Equipment Corporation DECsystem-2020 Image Removed was installed in the laboratory after we moved to the Park Building. We had been using the NIH's Division of Computer Research and Technology (DCRT) [now the Center for Information Technology (CIT)] DECsystem-10 time-shared system. As we used TOPS-10 operating system on the DECsystem-10, we installed TOPS-10 on the new DECsystem-2020. Bruce Shapiro had implemented a message-switching high-speed 9600-baud (normal speed was 300 or 1200 baud at the time) serial line multiplexor so we could move images and data to/from the DCRT system. However, the costs for the increasing amount of time we used on the DCRT system was escalating. For a cost comparable to renting time over a few years, we could purchase a dedicated system and have more compute power as well. So NCI supported us in purchasing the DECsystem-2020. This was a DEC Unibus system, which meant we could interface our hardware to this then-powerful 36-bit computer. In hindsight, this was one of the best procurements that Lew made. It offered us vastly better opportunities to interact with and manage the data that would not have been possible with a 9600 baud serial line. We could write software in the SAIL language, which meant we would have much more expressive power than we had with the PDP8e or PDP11 computers and could apply more advanced algorithms. This made a real difference in the productivity in analyzing real data with powerful algorithms.

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In addition to the RTPP, we acquired Comtal Image Removed image processor systems that had Q-bus type PDP11 interfaces. These in turn were interfaced to a PDP11/40 computer that was connected to the DECsystem-2020 via software called SPIDER, a virtual device driver network. SPIDER allowed PDP11 computers to be accessed from the DECsystem2020 without writing a new DECsystem-2020 driver for each new PDP11 device. Bruce Shapiro, our expert on PDP11s, wrote a time-shared packet switcher on the PDP11/40 to connect PDP11 devices to this network. I wrote the device driver on the DECsystem-2020 to access these devices and make them available for DECsystem-2020 application software. Images acquired using the RTPP could be analyzed on the Comtals; Bruce used this to help analyze his nucleic acid electron micrographs.

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Many software analysis systems were developed using the RTPP, especially in the area of 2D gels with the GELLAB-I system [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,24, 25, 26, 27, 28, 29, 30, 31, 32], a 2D gel exploratory data analysis system integrating the image-processing with statistical databases for multiple samples (myself); and RNA electron micrographs of secondary structure [10, 11, 32, 39, 48, 49] (Bruce Shapiro). After the RTPP was decommissioned, GELLAB-I was redeveloped as a portable software system using Unix/C/X-windows and was called GELLAB-II [42, 43, 44, 45] (see Lemkin's History of GELLAB Image Removed for more details, references, and history of GELLAB-II). Much of the work with GELLAB-I and GELLAB-II in exploratory data analysis led to its application to the DNA microarray domain (see http://maexplorer.sourceforge.net/ Image Removed) MAExplorer []. A third-generation instantiation of this data-mining system is part of the Open2Dprot open-source project at at http://open2dprot.sourceforge.net/ Image Removed with the goal of extending proteomics data mining to 2D LC-MS, protein-arrays. Bruce went on to develop other RNA analysis software [35, 39, 47, 48, 49, 50], leading to the StructureLab project [50] and related RNA structure analysis (see his RNA structure research group Image Removed).

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Details on the RTPP Design

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Div class desktop:grid-col-6 Image Modified Div class desktop:grid-col-6 Figure 4. The Real Time Picture Processor (RTPP) block diagram (reproduced with permission, from J. Histochem. Cytochem. [4], 1974). This shows additional parts of the system including a PDP11/20 message switcher to a PDP-10 Artificial Intelligence system PRDL (PRocedural Description Language) [5, TR-15] originally being developed on NIH's DCRT (now CIT) PDP-10 facility. The early microscope also had a 1024x1024 8-bit galvanometer scanner that could be used in place of the Quantimet 720 scanner. The later microscope was built around a Zeiss Axiomat microscope. An early high-quality grayscale display (Dicomed 31) was also used to make high-quality display images. Its functionality was replaced by the Quantimet grayscale buffer-memory display. The PDP8e accessed the RTPP using the BMON2 software [40, TR-21b]. The PDP-10 multiprocessor KL-10 system was a shared time-share computer at DCRT (now CIT). This was replaced in our design by a dedicated DECsystem-2020 when it became more cost-effective to have a dedicated computer. The DECsystem-2020 was a new microcoded processor that DEC was able to build for a fraction of the cost of the PDP-10. The PRDL [TR-15] and PROC10 [TR-8] image processing software were created to interface with the RTPP. We had considered creating a MAINSAIL(R)Image Removed compiler for use with the GPPASM (GPP assembler program) [TR-16] so that we could program the GPP in a SAIL-like language only available on large PDP-10 class systems. Later, a light box for films was used with the Quantimet vidicon scanner (see Figure 18) with changeable 35mm lenses (not shown in this block diagram - see Figure 5) to scan autoradiograph and wet 2D gels, RNA electron micrographs, and other transparencies.

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Div class desktop:grid-col-6 Div class desktop:grid-col-6 Figure 5. A simplified block diagram of the Real Time Picture Processor illustrating the two types of input and the microscope control from BMON2 paper [40], 1980. (Reprinted from Computer Programs in Biomedicine, vol 11, Lemkin P., Lipkin, L., BMON2 - A distributed monitor system for biological image processing, pp 21-42, Copyright (1980), with permission from Elsevier.) The PDP8e computer directed the microscope stage to positions determined either manually by the operator or by a list of positions defined by the user and then controlled by the computer. Images could be acquired by the buffer memories for processing by the BMON2 system. Raw images as well as processed images could be displayed on the Quantimet 720 CRT display. TV camera input was from either of the two TV cameras that were easily changed. The user interacted with the hardware using the control panel connected to the PDP8e using the BMON2 image processing software system.

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Div class desktop:grid-col-6 Image Modified Div class desktop:grid-col-6 Figure 6. RTPP Control Console was interfaced to the PDP8e and used to interact with the RTPP using the BMON2 buffer memory monitor operating system [40, TR-21, TR-21b]. See Figure 2 in [TR-21b] for the full description. It had various knobs (connected to A/D converters read by the PDP8e), lights for feedback, command buttons, toggle switches, and momentary toggle switches. Only some of these controls were used in the various programs, but having a variety of control options providing flexibility in the user interface. However, this was sometimes at the cost of added complexity and sometimes users had difficulty in learning the system because of this. ("All those knobs, buttons and switches!") However, this flexibility gave us the option of experimenting with various interaction modes that could then be optimized for particular analysis programs. This was before the computer mouse and graphical user interfaces became commonly available. (Click on this figure to bring up the high-resolution version of the figure. You may have to make your browser window larger.)

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Div class desktop:grid-col-6 Image Modified Div class desktop:grid-col-6 Figure 7. Photograph of the Quantimet-TV and control-console for the RTPP using the BMON2 software [40, TR-21, TR-21b, TR-23]. This was taken after we had moved the RTPP to the Park Building in Rockville, MD. (Reproduced from a figure with permission from Environmental Health Perspectives, 1980 []). The control desk had a microscope joystick (X,Y) and Z-axis (focus) control; knobs (connected to A/D converters read by the PDP8e), switches and lights that could be configured in various ways by the BMON2 software. The small box shown in the lower left allowed us to control the 4 edges of a frame as (X,Y) positions. It used four bi-directional two-level spring-loaded switches in a (North, South, East, or West) configuration. These switches came from the LINC-8 and were perfect for this type of control. This allowed us to easily control the direction of a cursor - much as is done today using the mouse, which did not exist at the time). Real-time video control was performed using the RTPP buffer memory controller hardware, which in turn was configured by the PDP8e. The control desk gave us a lot of flexibility - even if its complexity was sometimes compared to that of the starship Enterprise. Various programs (BMON2, FLICKER [13], LANDMARK in the GELLAB-I system [15, 17, 31], and others) could use that subset of the controls most appropriate for the particular application.

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The buffer memory image cards

The sample card shown below (front and back) illustrates the complexity of building large memory cards back in the early 1970s (Figures 8 through 10). Increases in chip memory capacity enabled enough memory to be put on a few cards to represent images with detail sufficient for meaningful biological image analysis. Before these new memory chips (the Texas Instruments TMS 4030 chip was a 4Kx1 bit dynamic RAM) were available, we had planned to construct the buffer memories using static shift-register memory chips (as George had done in the grain counter system). Total memory pixel size was 1 megabyte for the 64 boards - today 1 gigabyte of memory the size of a thumbnail sells for under $25 (on sale). Not only would the static shift-register memory chips have been more expensive, but also they also would not have had the random access performance we required in image processing, creating an inadequate design. The shift registers would have led to a slower, much smaller memory using more power for the same cost. The image pixels size and number of images in the buffer memories would have been less and many of the powerful software applications we used the RTPP for would not have worked as well or even been developed.

During this time, we had the conviction, led by Lew Lipkin and George Carman, that anything that we wanted to be do in software could be done by a series of sequential gates. These could be proved Boolean algebraically correct using Karnaugh MapsImage Removed, hardware finite state machines, and related techniques. George had just taken a microprogramming design course as part of his masters degree in computer hardware architecture and the design of buffer memories and the General Picture Processor (GPP) were perfect test beds in which to try out these new design principles which were relatively new for projects like this. Some of the design diagrams are shown in Figures 11 through 14 (from the Carman [4] paper). Figure 15 shows some examples of GPP microprogrammed instructions for manipulating the buffer memory data. The design was further described in some of the technical reports [TR-7, TR-7a, TR-16, TR-21, TR-21b, TR-22] listed at the end of this history. Because we were prototyping the system, the card was constructed using wire wrapping rather than multilayer printed circuit boards. A commercial version would have used printed circuit boards, but would only have been economically feasible if many copies of the RTPP were produced. Using complex multi-level printed circuit boards is generally too expensive for a research lab. 

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Div class desktop:grid-col-6 Image Modified Div class desktop:grid-col-6 Figure 8. Front of a buffer memory image card containing 64Kb x 16-bits of dynamic RAM constructed from 4Kx1 bit dynamic RAM chips (Texas Instruments part number TMS 4030) initially sold by Texas Instruments and later second-sourced by National Semiconductor and Signetics. Four boards constituted a 256x256x16-bit pixel sub-image. Either the high or low 8-bit byte (or neither) could be displayed. Each 256x256 sub-image could be positioned to any part of the 860x720 pixel TV screen. For many applications, to create a 512x512 image, four 256x256 sub-images were grouped to form a 512x512 image.

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Div class desktop:grid-col-6 Image Modified Div class desktop:grid-col-6 Figure 9. The 4Kx1 bit dynamic RAM or DRAM chip (part number TMS 4030) initially sold by Texas Instruments and second sourced by National Semiconductor, and Signetics (shown here). These were the first affordable (about $20 at the time) DRAMs available in large quantitities. Because chip vendors want to assure customers that the parts will always be available, they license other chip makers to "second source" interchangeable chips. Our memory boards are a mix of the black, silver, and gold colored chips because we used several vendors.

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Div class desktop:grid-col-6 Image Modified Div class desktop:grid-col-6 Figure 10. Back of a buffer memory image card containing 64Kb x 16-bits of dynamic RAM constructed from 4Kx1 bit dynamic RAM (part number TMS 4030) chips initially sold by Texas Instruments and second sourced by National Semiconductor and Signetics. There were over 3,000 wirewraps on each board. The initial card was designed and hand wired by George Carman, and Cambion Corporation replicated 63 additional cards with wirewrap wiring lists generated by George. Their automatic robots would position the board for each of the wrap positions and then wire that point. The photograph illustrates how easy it is to get lost in this forest of pins and wires. Doing this by hand would have been impossible. George felt that no other company could build the boards in the time frame with the essential quality control we required. He was right. Only one of the 63 the boards delivered was defective, which was amazing considering the complexity and number of boards. Because of the high frequency signals involved, George put small black decoupling capacitors on each board to "tune" it to minimize cross talk. So each board, then, was in some sense unique.

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Div class desktop:grid-col-6 Image Modified Div class desktop:grid-col-6 Figure 11. The RTPP buffer memory control logic (reproduced with permission from J. Histochem. Cytochem. [4], 1974). "Each buffer memory is an asynchronous device that received I/O requests either from the general picture process (GPP) or the Quantimet for input or output. Given a request and an address, it first checked to see whether the last (high order 14-bit address) four-word buffer accessed was the same as that for the current request. If so, it did not have to do another memory (RAM) cycle and the signal OLDBWB signal is 'true'. When a read cycle occurred and a different FWB was needed, it checked to see if the FWB was 'dirtied', in which case it must write it back into the memory before the next current request could be proceed. Being dynamic RAMs, they must be refreshed (logic not shown) so as not to lose the data."

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Fig-RTPP-GPP-bus-structure Fig-RTPP-GPP-bus-structure

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Div class desktop:grid-col-6 Div class desktop:grid-col-6 Figure 12. The RTPP general picture processor (GPP) bus structure (reproduced with permission from J. Histochem. Cytochem. [4], 1974). "The instruction addressing sequence is done serially. That is, Pi is addressed, then P2, then P3. Let 'c(.)' denote 'contents of current memory location'. If any address is immediate, no memory fetch is done. Rather, the PM data, c(P), is enabled onto the data bus DB. If direct addressing mode c(c(P)) is used, the PM data c(P) is enabled onto the data address bus, DAB, and then loaded onto the appropriate data field address register. The memory then enables its data, c(c(P)), onto the data base, DB. If indirect mode is used then the same sequence is repeated as for direct mode, but c(c(P)) is enabled back onto the DAB instead of the DB. Then the data address field register addressed is loaded and the c(c(c(P))) from that memory is enabled onto the DB. A conflict may occur in the use of the indirect mode from the 'MOVE' instruction. This is resolved by storing the source data in the data bus register, DBR, temporarily. Various devices and memories are connected to the bus structure and interact when the control section activates them. The average GPP instruction time is designed to be on the order of 250 nanoseconds." (Click on this figure to bring up the high-resolution version of the figure. You may have to make your browser window larger.)

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Div class desktop:grid-col-6 Image Modified Div class desktop:grid-col-6 Figure 13. The RTPP triple line buffer logic (reproduced with permission from J. Histochem. Cytochem. [4], 1974). "The RTPP was designed to do 3x3 neighborhood image-processing in parallel in the GPP. Associated with the three lines is an effective Y dynamic address used to order the three lines as to (Y-1,Y,Y+1). In reading a raster line pattern into the triple line buffer, the oldest line must be replaced with the newest line. Similarly, the other two lines need to be adjusted as (Y-1,Y,Y+1) to (Y,Y+1,Y+2). By selecting the effective line address with a modulo three dynamic Y address counter, a dynamic Y address can be implemented. This is similar to the concept of buffer. The three X dynamic address vectors point to 3x3 neighborhood arrays in the line buffer. This neighborhood is called the current neighborhood. All of the dynamic address vectors are easily and efficiently programmed in the GPP to tessellate the current neighborhood along the three lines in the line buffer."

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Fig-RTPP-GPP-control-logic-FSM Fig-RTPP-GPP-control-logic-FSM

Figure 14. The RTPP GPP control logic finite state machine (reproduced with permission from J. Histochem. Cytochem. [4], 1974). "The GPP control logic is implemented as a finite state machine where the states of the system are defined from the logic flow of the system. This consists of the various bus, register enable and load signals. The state is a function of the current state and the current operator. Thus, to extend the machine, additional states and transitions between states would have been added (see [TR-7,TR-22])."

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Fig-RTPP-Examples-of-GPASM-code Fig-RTPP-Examples-of-GPASM-code

Figure 15. The Examples of RTPP instructions for the GPP (reproduced with permission from J. Histochem. Cytochem. [4], 1974). The Pi refers to a 3x3 pixel neighborhood that would be tessellated through the entire image. The GPP instructions [A HREF="#TR-22">TR-22] could be compiled by the GPPASM [A HREF="#TR-16">TR-16] assembler program running on the PDP8e and then loaded into the GPP instruction memory. A debugger for the GPP was DDTG that ran on the PDP8e [A HREF="#TR-2">TR-2] , but controlled the GPP and buffer memories. We had also been evaluating collaborating on the construction of a a MAINSAIL(R) Image Removed compiler to generate GPP assembly code so we could program the RTPP in a SAIL-like language.

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Another of the projects Lew and I were also working on was the construction of a 3D brain atlas of an anolus lizard brain using aligned microtomed serial-section images. (Some of the goals for that project were similar to that of the National Library of Medicine's Visible Human. However, this was well before adequate computer technology and resources were available to implement such an atlas.) We wrote a PDP8e program to move the optical microscope stage in (X,Y) while keeping the center of the brain in the scanned visual center of the image field as we switched slides in a series of microtomed serial sections (the Z-axis control was not used in this operation). Each centered image could then be captured and saved as a disk file. The next section visible on the TV camera was compared with the image previously captured and stored in the image buffer memory. This procedure was iteratively repeated with subsequent slides to capture a sequence of aligned serial sections from a set of slides. The buffer memory data was saved at each point on 9-track magnetic tape. (This alignment software subsequently led to our involvement with 2D electrophoretic gels analysis [discussed below].) The set of serial sections could then be re-accessed sequentially to step through the brain slices centered at the selected point. We could generate movie loops with the BMON2 software to move virtually up and down through the serial sections at various frame rates. Because we could store sixteen 256x256 images in the buffer memory, the loops could have up to 16 sections and allowed us to visualize the 3D structure of part of the brain.

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Macrophage-with-Amosite-24Hr-phase-contrast Macrophage-with-Amosite-24Hr-phase-contrast

Figure 16. Photomicrograph of P388D1 macrophage-like cells 24 hours after amosite asbestos treatment used to study fiber-induced cytotoxicity [9] (reproduced with permission from Environmental Health Perspectives, 1980).

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Figure 17. (Left) Boundary trace transform (BTT) of 233 images of 15-second interval scans of a single living P388D1 macrophage-like cell (left) (reproduced with permission from Environmental Health Perspectives, 1980 [9]). The boundaries for this set of images were traced by hand using a graphics tablet connected to the RTPP. The BTT is a 2D boundary frequency histogram where darker (higher frequency) pixels indicate boundaries of the cell that are more adherent to the glass slide and have less motility. BMON2 captured the set of images data and double buffered them to 9-track magnetic tape, with a 15-second image-sampling interval between scans. (Right) Illustration of a single cell captured by the RTPP using differential interference optics. The algorithm is described in several papers [8, 9]. Movies were made on the RTPP of a subsequence of 16 of the images in which you could see the cell trying to ingest the fiber, the fiber breaking through the other side of the cell (membrane), and then the cell backing up to try to reingest that part of the fiber, etc. These images allowed us to create a probability distribution of adhesion strength for boundary points of amoeboid cells. Points with low probability would flutter and extend. Looking at individual boundaries would not reveal this type of information; it was the ability to integrate large quantities of data that allowed these patterns to be detected. This was the way we thought the system should have been used - finding interesting results when no other method for doing so was possible.

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The FLICKER software allowed users to measure spots as a set of (X,Y) image positions and integrated-densities for each sample. We manually recorded this data for later analysis, manually defining spots to be corresponding if they aligned well with FLICKER.

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lightBoxCameraStation lightBoxCameraStation

Figure 18. This was the alternative image acquisition setup. (Reproduced from a figure with permission from a reprint from Environmental Health Perspectives, 1980 [9].) A high-quality uniform illumination Aristo light box and Quantimet Vidicon TV camera were used for non-microscope images. A gel autoradiograph, wet 2D gel, electron micrograph, or other transparent sample object was placed on the light box and scanned using the RTPP/Vidicon camera. A NBS standard neutral density step wedge was placed on the bottom of the scan area. This was captured along with the image and was used to calibrate the grayscale pixel data to optical density using a piecewise linear curve fitting algorithm (see [9] for an example). As an aside, the electronics workbench area in the background was where many of the local RTPP electronics assembly was performed in the Park Building.

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Eric painstakingly generated paired data for about 1,400 spots from the segmented images and their paired spot lists for a few gels. Because of the difficulty in matching or pairing spots between gels, I also developed spot-pairing and spot "landmarking" programs, which ran interactively on the RTPP/PDP8e. (Landmarking is visually identifying a set of spots that are common in both the reference gel and each additional gel sample so spot pairing could proceed.) Eric then subjected the data to SPSS Image Removed statistical analysis with encouraging results (t-Tests, Spearman correlation, ANOVA) and it was published in [14] and enhancements in [15,18-21]. All three of these programs were rewritten in SAIL for the DECsystem-2020. At this point we realized that we wanted to build a database containing large numbers of gels to detect marker proteins or classify samples by protein pattern signatures indicating states of differentiation, disease conditions, or other experimental conditions. This was the basis of GELLAB-I.

This led to the SAIL program CGELP, in GELLAB-I, to construct a composite gel database with a virtual reference gel [14-18,20,30] and the addition of many more statistical methods. (The subsequent Unix version was called CGELP2 [30, 42, 43, 44, 45] where additional statistical exploratory data analysis methods were added - see [history of GELLAB Image Removed].) Spots of a set of N-1 gels would be matched to one of the gels called a reference gel and spots missing in the physical reference gel would be extrapolated into the reference gel. Figure 19 shows the reference gel 324.1 that was an acute myeloid leukemia (AML) gel, scanned with the RTPP. This reference gel was used in many of the leukemia databases to tie the data together [14, 15, 16, 17, 18, 22]. The collection of SAIL programs, as well as their RTPP interface, was called GELLAB-I. After leaving NIH (for the University of Chicago), Eric would fly back to work in our laboratory to do marathon late-night landmarking sessions to help generate these databases of large numbers of 2D leukemia gels. Over the years, we had built various databases with over 400 gel samples. The leukemia database had over 130 samples. Some of these gel sample images are available on the bioinformatics.org/lecb2dgeldb Image Removed open source repository. This early research led to my interest in exploratory data analysis and future work with microarrays with MAExplorer.sourceforge.net Image Removed [46], and proteomics exploratory data analysis using open2dprot.sourceforge.net Image Removed.

Peter Sonderegger, while a post-doc at the National Institute of Child Health and Development (NICHD), used the GELLAB-I system with the RTPP to investigate how the expression of axonal proteins of sensory and motor neurons was influenced by non-neuronal cells [27, 29, 45]. At the same time we were investigating the feasibility of porting GELLAB-I (written in SAIL) to the PASCAL computer language. The inflexibility of PASCAL eventually led us to convert GELLAB-I to the portable C/UNIX/X-windows environment called GELLAB-II [42, 43, 44, 45] The DECsystem-10 SAIL version, GELLAB-I, was exported to research labs at Univ. of Chicago (Eric Lester) and Univ. of Kiel (Heinz Busse). The Unix version, GELLAB-II, was exported to a number of research labs around the world (CDC with Jim Myrick [44], Univ. Zurich with Peter Sonderegger, Agr. Univ. Norway with Trygve Krekling, and others) and led to a commercial subset version for Windows PCs called GELLAB-II++ by CSPI/Scanalytics.

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Heme-AML-2Dgel-Lester Heme-AML-2Dgel-Lester

Figure 19. One of the early 2-dimensional (2D) gels scanned with the vidicon/RTPP system (leukemia AML sample number 324.1 - a 2D-gel autoradiograph scanned to a 512x512 8-bit image) in a collaboration with Eric Lester (NCI oncologist at the time), Lewis Lipkin, and myself with the GELLAB-I system [14, 15, 16, 17, 18, 22]. The film was scanned on a light box (shown in Figure 18 above) along with a neutral-density step wedge at the top so the grayscale image data could be mapped to optical density, resulting in a more linear calibration with protein concentration in the 2D gel. The leukemia gels are part of a public 2D gel database at http://bioinformatics.org/lecb2dgeldb Image Removed.

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UseOfRTPPforRNAsecondaryStructure UseOfRTPPforRNAsecondaryStructure

Use of the RTPP for RNA secondary structure analysis

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Partly as a result of this collaboration, Jake became more interested in computing, which led him to purchase one of the early DEC VAX computers for his lab. As Jake became more involved with computational techniques, he realized the general importance, as did Lew, of using computers in biology. Eventually, this interest culminated with the National Cancer Institute's purchase of a Cray XMP supercomputer, and the establishment of what is today the Advanced Biomedical Computer Center in Frederick. The Cray XMP, at that time, was the first supercomputer in the world solely dedicated to biomedical research. Thus, the impact of the RTPP continues to be felt in the biological computation sciences 30 years later.

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RNAelectronMicrograph-Shapiro-Maizel RNAelectronMicrograph-Shapiro-Maizel

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Figure 20. One of the early RNA electron micrographs scanned with the vidicon/RTPP system (Jacob Maizel, Bruce Shapiro, and Lewis Lipkin) [33, 34, 39, 48, 49]. The sample was adenovirus type 2 messenger RNA. Bruce developed boundary segmenters and boundary shape descriptors that could map electron micrograph data to the secondary structure.

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JournalReferences JournalReferences

Journals:

1. Anchor
   Lipkin66 Lipkin66

   Lipkin, L.E., Watt, W.C., Kirsch, R.A.: The analysis, synthesis, and description of biological images. Ann N Y Acad Sci. 128(3): 984-1012, 1966.

2. Anchor
   Lipkin74 Lipkin74

   Lipkin, L.E., Lemkin, P.F., Carman, G.: Automated autoradiographic grain counting in human determined context. J. Histochem. Cytochem. 22(7): 755-765, 1974. (PDF Image Removed)

3. Anchor
   RTPP-JHC-I-paper RTPP-JHC-I-paper

   Lemkin, P.F., Carman, G., Lipkin, L., Shapiro, B., Schultz, M., Kaiser, P.: A real time picture processor for use in biologic cell identification. I. System design. J. Histochem. Cytochem. 22(7): 725-731, 1974. (PDF Image Removed)

4. Anchor
   RTPP-JHC-II-paper RTPP-JHC-II-paper

   Carman, G., Lemkin, P.F., Lipkin, L., Shapiro, B., Schultz, M., Kaiser, P.: A real time picture processor for use in biologic cell identification. II. Hardware implementation. J. Histochem. Cytochem. 22(7): 732-740, 1974. (PDF Image Removed)

5. Anchor
   PRDL-ECR-paper PRDL-ECR-paper

   Shapiro, B., Lemkin, P.F., Lipkin, L.: The application of artificial intelligence techniques to biologic cell identification. J. Histochem. Cytochem. 22(7): 741-750, 1974. (PDF Image Removed)

6. Anchor
   Schultz74 Schultz74

   Schultz, M.L., Lipkin, L.E., Wade, M.J., Lemkin, P.F., Carman, G.M.: High resolution shading correction. J. Histochem. Cytochem.22(7): 751-754, 1974. (PDF Image Removed)

7. Anchor
   Shapiro71 Shapiro71

   Shapiro, H.M., Bryan, S.D., Lipkin, L.E., Stein, P.G., Lemkin, P.F.: Computer-aided microspectrophotometry of biological specimens. Exp Cell Res. 67(1): 81-89, 1971.

8. Anchor
   Lemkin79a Lemkin79a

   Lemkin, P.F.: The boundary trace transform: An edge and region enhancement transform. Comp. Graphics Image Processing 9: 150-165, 1979.

9. Anchor
   Lemkin80a Lemkin80a

   Lemkin, P.F., Lipkin, L., Merril, C., Shiffrin, S.: Protein abnormalities in macrophages bearing asbestos. Environ. Health Perspect. 34: 5-89, 1980. (PDF)

10. Anchor
    Lemkin80b Lemkin80b

    Lipkin, L.E.: Cellular effects of asbestos and other fibers: correlations with in vivo induction of pleural sarcoma. Environ. Health Perspect. 34:91-102, 1980. (PDF)

11. Anchor
    Lemkin79b Lemkin79b

    Lemkin, P.F.: An approach to region splitting.   Comp. Graphics Image Processing 10: 281-288, 1979.

12. Anchor
    Lemkin79c Lemkin79c

    Lemkin, P.F., Lipkin, L.: Use of the positive difference transform for RBC elimination in bone marrow smear images. Anal. Quant. Cytol. 1(1): 67-76, 1979.

13. Anchor
    Lemkin79d Lemkin79d

    Lemkin, P.F., Merril, C., Lipkin, L., Van Keuren, M., Oertel, W., Shapiro, B., Wade, M., Schultz, M., Smith, E.: Software aids for the analysis of 2D gel electrophoresis images. Comput. Biomed. Res. 12: 517-544, 1979.

14. Anchor
    Lemkin80c Lemkin80c

    Lester, E.P., Lemkin, P.F., Cooper, H.L., Lipkin, L.E.: Computer-assisted analysis of two-dimensional electrophoresis of human peripheral blood lymphocytes. Clin. Chem. 26: 1392-1402, 1980. (PDF Image Removed)

15. Anchor
    Lemkin80d Lemkin80d

    Lipkin, L.E., Lemkin, P.F.: Data base techniques for multiple PAGE (2D gel) analysis. Clin. Chem. 26: 1403-1413, 1980. (PDF Image Removed)

16. Anchor
    Lemkin81a Lemkin81a

    Lemkin, P.F., Lipkin, L.: GELLAB: A computer system for 2D gel electrophoresis analysis. I. Segmentation and preliminaries. Comput. Biomed. Res. 14: 272-297, 1981.

17. Anchor
    Lemkin81b Lemkin81b

    Lemkin, P.F., Lipkin, L.: GELLAB: A computer system for 2D gel electrophoresis analysis. II. Spot pairing. Comput. Biomed. Res. 14: 355-380, 1981.

18. Anchor
    Lemkin81c Lemkin81c

    Lemkin, P.F., Lipkin, L.: GELLAB: A computer system for 2D gel electrophoresis analysis. III. Multiple gel analysis. Comput. Biomed. Res. 14: 407-446, 1981.

19. Anchor
    Lemkin81d Lemkin81d

    Lester, E.P., Lemkin, P.F., Lipkin, L.E.: New dimensions in protein analysis - 2D gels coming of age through Image Processing.   Anal. Chem. 53: 390A-397A, 1981.

20. Anchor
    Lemkin81e Lemkin81e

    Lester, E.P., Lemkin, P.F., Lipkin, L.E., Cooper, H.L.: A two-dimensional electrophoretic analysis of protein synthesis in resting and growing lymphocytes in vitro. J. Immunol. 126: 1428-1434, 1981.

21. Anchor
    Lemkin82a Lemkin82a

    Lemkin, P.F., Lipkin, L.E., Lester, E.P.: Some extensions to the GELLAB 2D electrophoresis gel analysis system. Clin. Chem. 28: 840-849, 1982. (PDF Image Removed)

22. Anchor
    Lester82a Lester82a

    Lester, E.P., Lemkin, P.F., Lipkin, L.E.: A two-dimensional gel analysis of autologous T and B lymphoblastoid cell lines. Clin. Chem.28: 828-839, 1982. (PDF Image Removed)

23. Anchor
    Lester82b Lester82b

    Lester, E.P., Lemkin, P.F., Lowery, J.F., Lipkin, L.E.: Human leukemias: A preliminary 2D electrophoretic analysis.   Electrophoresis 3: 364-375, 1982.

24. Anchor
    Howard83 Howard83

    Howard, R.J., Aley, S.B., Lemkin, P.F.: High resolution comparison of Plasmodium Knowlesi clones of different variant antigen phenotypes by 2D gel electrophoresis and computer analysis.   Electrophoresis 4: 420-427, 1983.

25. Anchor
    Lemkin83a Lemkin83a

    Lemkin, P.F., Lipkin, L.E.: 2D Electrophoresis gel data base analysis: Aspects of data structures and search strategies in GELLAB.   Electrophoresis 4: 71-81, 1983.

26. Anchor
    Lester83a Lester83a

    Lester, E.P., Lemkin, P.F., Lipkin, L.E.: States of differentiation in leukemias: A 2D gel analysis. In Rowley, J. D. and Ultmann, J. E. (Eds.): Proceedings of 5th Annual Bristol Myers Symposium on Cancer Research.   Chromosomes and Cancer: From Molecules to Man. New York, Academic Press, 1983, pp. 226-245.

27. Anchor
    Lemkin84a Lemkin84a

    Lemkin, P.F., Sonderegger, P., Lipkin, L.: Identification of coordinate pairs of polypeptides: A technique for screening of putative precursor product pairs in 2D gels.Clin. Chem. 30: 1965-1971, 1984. (PDF Image Removed)

28. Anchor
    Lester84a Lester84a

    Lester, E.P., Lemkin, P F., Lipkin, L.E.: Protein indexing in leukemias and lymphomas. Ann. N.Y. Acad. Sci. 428: 158-172, 1984.

29. Anchor
    Sonderegger85 Sonderegger85

    Sonderegger, P., Lemkin, P.F., Lipkin, L., Nelson, P.: Differential modulation of the expression of axonal proteins by non-neuronal cells and the peripheral and central nervous system. EMBO J. 4: 1395-1401, 1985. (PDF)

30. Anchor
    Lemkin81f Lemkin81f

    Lemkin, P.F., Lipkin, L.E.: GELLAB: Multiple 2D electrophoretic gel analysis. In Allen, R. and Arnaud (Eds.):   Electrophoresis '81. New York, W. De Gruyter, 1981, pp. 401-411.

31. Anchor
    Lemkin83b Lemkin83b

    Lemkin, P.F. , Lipkin, L.E.: Database techniques for 2D electrophoretic gel analysis. In Geisow, M. and Barrett, A. (Eds.):   Computing in Biological Science. North Holland, Elsevier, 1983, pp. 181-226.

32. Anchor
    Lester84a Lester84a

    Lester, E.P., Lemkin, P.F.: A 'GELLAB' computer assisted 2D gel analysis of states of differentiation in hematopoietic cells. In Neuhoff, V. (Ed.):   Electrophoresis '84. Chemie, Springer-Verlag, 1984, pp. 309-311.

33. Anchor
    Lemkin79d Lemkin79d

    Lemkin, P.F., Shapiro, B., Lipkin, L., Maizel, J., Sklansky, J., Schultz, M.: Preprocessing of electron micrographs of nucleic acid molecules for automatic analysis by computer. II. Noise removal and gap filling. Comput. Biomed. Res. 12: 615-630, 1979.

34. Anchor
    Lipkin79b Lipkin79b

    Lipkin, L., Lemkin, P.F., Shapiro, B., Sklansky, J.: Preprocessing of electron micrographs of nucleic acid molecules for automatic analysis by computer. Comput. Biomed. Res. 12: 279-289, 1979.

35. Anchor
    Shapiro77a Shapiro77a

    Shapiro, B., Lipkin L.: The circle transform, an articulable shape descriptor. Comput. Biomed. Res. 10: 511-28, 1977.

36. Anchor
    Shapiro77b Shapiro77b

    Shapiro, B.: Language processor generation with BNF inputs: methods and implementation. Comp. Programs. Biomedicine 7:85-98, 1977.

37. Anchor
    Shapiro79a Shapiro79a

    Shapiro, B., Pisa, J., Sklansky, J.: Skeletons from sequential boundary data.   Proc. Intl. Conf. On Pattern Recognition and Image Processing. IEEE Comp. Soc. Press, Los Angeles, CA., 265-270, 1979.

38. Anchor
    Shapiro81a Shapiro81a

    Shapiro, B., Pisa, J., Sklansky, J.: Skeleton generation from xy boundary sequences.   Comp. Vision Graphics Image Processing 15(2) 136-153, 1981.

39. Anchor
    Shapiro79b Shapiro79b

    Shapiro, B.S., Lipkin, L.E., Maizel, J.V.: Computerized generation of secondary structure maps for nucleic acids. Comp. Biomed. Res.12(6):545-568, 1979.

40. Anchor
    BMON2-CPIB-paper BMON2-CPIB-paper

    Lemkin, P.F., Lipkin, L.: BMON2 - A distributed monitor system for biological image processing. Computer Programs in Biomedicine 11: 21-42, 1980. (PDF)Reprinted from COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, Vol 11, Lemkin PD and LipkinL, BMON2 - A distributed monitor system for biological image processing, Pages 21-42, Copyright (1980), with permission from Elsevier.

41. Anchor
    Lipkin70 Lipkin70

    Lipkin, B.S., Rosenfeld, A. (Eds):   Picture Processing and Psychopictorics. Academic Press, New York, 1970, pps 526.

42. Anchor
    Lipkin89g Lipkin89g

    Lemkin, P.F.: GELLAB-II: A workstation based 2D electrophoresis gel analysis system. In Endler, T. and Hanash, S. (Eds.):   Proceedings of 2D Electrophoresis. West Germany, VCH Press, 1989, pp. 52-57. (This was the announcement of GELLAB-II)

43. Anchor
    Lipkin89h Lipkin89h

    Lemkin, P.F., Lester, E.P.: Database and search techniques for 2D gel protein data: A comparison of paradigms for exploratory data analysis and prospects for biological modeling. Electrophoresis 10(2): 122-140, 1989.

44. Anchor
    Robinson95 Robinson95

    Robinson, M.K., Myrick, J.E., Henderson, L.O., Coles, C.D., Powell, M.K., Orr, G.A., Lemkin, P.F.: Two-dimensional protein electrophoresis and multiple hypothesis testing to detect potential serum protein biomarkers in children with fetal alcohol syndrome. Electrophoresis 16: 1176-1183, 1995.

45. Anchor
    Stoeckli89 Stoeckli89

    Stoeckli, E.T., Lemkin, P.F., Kuhn, T.B., Ruegg, M.A., Heller, M., Sonderegger, P.: Identification of proteins secreted from axons of embryonic dorsal-root-ganglia neurons. Eur. J. Biochem. 180: 249-258, 1989.

46. Anchor
    Lemkin00a Lemkin00a

    Lemkin, P.F., Thornwall, G., Walton, K., Hennighausen, L: The Microarray Explorer tool for data mining of cDNA microarrays - application for the mammary gland, Nucleic Acids Res. 20(22): 4452-4459, 2000.

47. Anchor
    Shapiro88 Shapiro88

    Shapiro, B.A.: An algorithm for comparing multiple RNA secondary structures. Comput. Appl. Biosci. 4(3): 387-393, 1988.

48. Anchor
    Margalit89 Margalit89

    Margalit, H., Shapiro, B.A., Oppenheim, A.B., Maizel, J.V. Jr.: Detection of common motifs in RNA secondary structures. Nucleic Acids Res. 17(12): 4829-4845, 1989.

49. Anchor
    Le89 Le89

    Le, S.Y., Owens, J., Nussinov, R., Chen, J.H., Shapiro, B., Maizel, J.V.: RNA secondary structures: comparison and determination of frequently recurring substructures by consensus. Comput. Appl. Biosci. 5(3): 205-210, 1989.

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    Shapiro96 Shapiro96

    Shapiro, B.A., Kasprzak, W.: STRUCTURELAB: a heterogeneous bioinformatics system for RNA structure analysis. J Mol. Graph.14(4): 194-205, 222-224, 1996.

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These reports were archived in the U.S. Department of Commerce's National Technical Information Service (NTIS) in Springfield VA. They currently offer online reports from 1990 on their web site http://www.ntis.gov/, although older reports can be ordered. Some additional reports appeared as University of Maryland Computer Science Center technical reports.

• Anchor
  TR-2-report TR-2-report

  TR-2. Lemkin, P.F.: DDTG - Functional specification for the RTPP monitor. NCI/IP TR-2, 2-5-1976. NTIS Accession No. PB250726/AS, Springfield, VA, 1976, 90 pp. (Also in DECUS No. 8-823). (PDF)

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  TR-7-report TR-7-report

  TR-7. Lemkin, P.F., Carman, G., Lipkin, L., Shapiro, B., Schultz, M.: Real time picture processor: Description and specification. NCI/IP TR-7, 2-31-1976. NTIS Accession No. PB252268/AS, Springfield, VA, 1976, 139 pp. (PDF)

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  TR-7a-report TR-7a-report

  TR-7a. Lemkin, P.F.: Real Time Picture Processor: Description and specification. TR-7a, 6-23-1977. NTIS Accession No. PB269600/AS, Springfield, VA, 1977, 185 pp. (PDF TR-7a)

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  TR-8-report TR-8-report

  TR-8. Lemkin, P.F., Shapiro, B., Gordon, R., Lipkin, L.: PROC10 - An image processing system for the PDP10: Description and specification. NCI/IP TR-8, 12-16-1976. NTIS Accession No. PB261535/AS. Springfield, Va., 1976, 53 pp. (Also in DECUS No. 10-270). (PDF)

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  TR-15-report TR-15-report

  TR-15. Shapiro, B., Lemkin, P.F.: PRDL - Procedural Description Language. NCI/IP TR-15, 10-10-1977. NTIS Accession No. PB273112/AS Springfield, Va., 1977, 23 pp. (PDF)

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  TR-16-report TR-16-report

  TR-16. Lemkin, P.F., Shapiro, B., Schultz, M., Lipkin, L., Carman, G.: GPPASM - A PDP8e assembler for the General Picture Processor. NCI/IP TR-16, 12-15-1976. NTIS Accession No. PB261537/AS, Springfield, VA, 1976, 45 pp. (PDF)

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  TR-21-report TR-21-report

  TR-21. Lemkin, P.F.: Buffer memory monitor system for interactive image processing. NCI/IP TR-21, 3-31-1976. NTIS Accession No. PB261536/AS, Springfield, VA, 1976, 26 pp. (PDF)

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  TR-21b-report TR-21b-report

  TR21-b. Lemkin, P.F.: BMON2 - buffer memory monitor system for interactive image processing. NCI/IP TR-21b, 3-17-1978. NTIS Accession No. PB269642/AS, Springfield, VA, 1978, 112 pp. (PDF)

• Anchor
  TR-22-report TR-22-report

  TR-22. Carman, G., Lemkin, P.F., Schultz, M., Lipkin, L., Shapiro, B.: Microprogram control architecture for the General Picture Processor. NCI/IP TR-22, 4-22-1977. NTIS Accession No. PB269762/AS, Springfield, VA, 1977, 35 pp. (PDF)

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  TR-23-report TR-23-report

  TR-23. Lemkin, P.F.: BMOMNI - Fortran interface program for the RTPP buffer memory, Quantimet and control desk. NCI/IP TR-23, 12-14-1976. NTIS Accession No. PB261538/AS, Springfield, VA, 1976, 10 pp. (PDF)

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  TR-472-report TR-472-report

  TR-472. Shapiro, B.: The use of orthogonal expansion for biological shape description. College Park, MD, University of Maryland Computer Science Center TR-472, Aug. 1976, pp 30. TR-653. Lemkin, P.F.: Bone marrow smear image analysis. College Park, MD, University of Maryland Computer Science Center TR-653, April, 1978, 156 pp. (PDF)

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  TR-655-report TR-655-report

  TR-655. Lemkin, P.F.: The run length map: A representation of contours and regions for efficient search and low level semantic encoding. College Park, MD, University of Maryland Computer Science Center TR-655, April, 1978, 60 pp. (PDF)

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  TR-BAS78-report TR-BAS78-report

  TR-BAS78. Shapiro, B.S.: "Shape description using boundary sequences", U. Maryland Computer Science Dept, 1978. (Ph.D. dissertation).

...

Peter F. Lemkin, Lemkingroup.com Image Removed

(Note: You may also access the PDF and journal articles on the lemkingroup.com RTTP history mirror Image Removed.)
Original: 02/25/2007, Version #57 - original released to History of NIH
Revised: 9/5/2011, Version: #59 - fixed missing links and navigation change
Content transferred from html to confluence: Spring 2019, Fixed footnote page anchors that weren't functioning.