2007 Materials for NCBC Program Review - Revision history

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6. What changes could make the program more effective in the future?

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Tkapur: /* '''Q3:A list of publications and/or software tools produced by the Center.''' If this information is provided in your progress report or is available on your website, a link will be sufficient. We

2007-06-08T18:34:13Z

/* '''Q3:A list of publications and/or software tools produced by the Center.''' If this information is provided in your progress report or is available on your website, a link will be sufficient. We

Tkapur: /* '''Q3:A list of publications and/or software tools produced by the Center.''' If this information is provided in your progress report or is available on your website, a link will be sufficient. We

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/* '''Q3:A list of publications and/or software tools produced by the Center.''' If this information is provided in your progress report or is available on your website, a link will be sufficient. We

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 We believe that the program could be made more effective in the future by focused effort on three fronts: an increase in the national level visibility for the program, preservation of the local autonomy of the center leadership, and stability in the funding of the centers. Below we expand on each of these three suggestions.
-Increase in National Visibility
+===Increase in National Visibility===
 The overall objective statement of the NCBC program calls for building computational infrastructure for the nation's biomedical research efforts -- this ambitious goal includes both computational and biomedical science, areas in which the existing centers have extensive experience, but also in nationwide "marketing" efforts where the scientific community is less adept.  Several centers, including NA-MIC, have developed novel approaches to this problem through their training and dissemination cores, but as the output of the centers grows along with the number of potential users in the community and the potential impact, these critical resources will be increasingly strained.  There are several approaches the overall program could take to address this issue including supplemental funding to host workshops or conferences, providing small travel grants for researchers or students to visit the centers, or actively encouraging a wider range of NIH funded researchers to adopt the tools generated by the NCBCs.  In particular, collaboration PAR has been very effective as a mechanism for encouraging busy scientists to consider adopting the NCBC tools and is an excellent example of how the program can extend the impact of the basic investment in scientific infrastructure.
-Preservation of Local Autonomy
+===Preservation of Local Autonomy===
 The program should avoid adding extra layers of uniformity to what are fundamentally unique centers.  The NCBC program has successfully established a distributed network of centers drawing on the expertise of some of the nation's leading researchers drawn to the program for the opportunity to develop and apply their know-how to this ambitious effort.  This rich environment, predictably, yields a diversity of approaches and organizational structures as each of the centers works to implement their particular vision of how to fulfill the overall mission of the NCBC program.  Preserving the vitality of the effort depends on retaining this autonomy as each center strives to meet the individual objectives suited to their communities.  The program needs well defined goals that each center must meet, but the overall program should facilitate the individual solutions of the center's leadership.
-Stability in Funding
+===Stability in Funding===
 One critical mission of the NCBC program is the creation of infrastructure. These large-scale efforts require time-horizons that are incompatible with the current framework of many programs at NIH. It might take two or three iterations until a software package is sufficiently mature to be attractive to a larger community of scientists. Large software platforms require dedicated engineering staff of 10-20 full-time employees in addition to the biomedical scientists developing functionality aimed at solving a particular problem. Many of the NCBCs are working on several packages. This results in underfunded projects, which compromises the timeliness and performance of the resulting software.
 It would be advisable to increase funding for the engineering and outreach activities of the centers and provide the funding in a reliable way. The continous stream of cuts from of the original budget has made this discrepancy even more pronounced. In 2007/2008 we will receive only 77.7% of the money that was budgeted in the application for that year. Following the RFA guidelines, the original budget did not contain adjustments for inflation. Furthermore, in deviation from the way that most NIH programs are funded, the budget was frozen in total dollars not direct dollars. Institutional overhead rates, and fringe and benefit rates have increased for several of the NA-MIC participants during the last three years and have resulted in further decreases in the amount of money available to actually do research.
 . What lessons have been learned from the NCBC initiative that can guide future NIH efforts in biomedical computing?
 Among the main lessons learned in this initial stage of the NCBC program, is the fact that Center startup time is greater than anyone anticipated, the learning curve is steeper, and developing robust software for advanced applications is more difficult than anticipated. We have also learned that algorithms development is better served as an iterative rather than sequential process, and as mentioned earlier, in order to maximize our chances of success, the scope of work and the level of funding must be in alignment. Below we expand on each of these points.
-Greater Start Up Time and Steeper Learning Curve Than Anticipated
+===Greater Start Up Time and Steeper Learning Curve Than Anticipated===
 Bringing together computer scientists, engineers, and biomedical researchers, with diverse interests, training, and background, for the purpose of working on a set of biological problems, is no easy feat and, in retrospect requires a steeper learning curve than was anticipated. This steeper learning curve is understandable, since the main focus initially was on developing alliances among cores in order to increase awareness regarding the kinds of tools needed for the specific imaging problems posed by the biomedical researchers. The first year of the grant, as noted in our annual report, reflected a "core" emphasis. It was not until the second year that the focus shifted to a focus on "themes", which cut across "core" boundaries. While this shift was viewed as part of a natural evolution, this can help guide future NIH efforts by where we should begin new Centers by suggesting that specific projects/clinical applications be highlighted in the first few months of the Center, based on meetings among core members, so as to facilitate a focus on clinical applications from the outset.
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 Such an early emphasis on clinical applications/problems would facilitate an early focus on the development and application of computational tools, which could be more closely aligned with specific clinical problems and applications.This would breakdown artificial barriers that a "core" focus involves, which, while seemingly an inherent part of the initial stages, could be curtailed. In this way, the needed applications of the driving biological problems could form natural groupings that involve members from all cores, and work groups could be set up that reflect a "theme"/"application" approach. This would also assist in more communication between cores, which would also facilitate ongoing communication among computer scientists, engineers, and biomedical researchers.
-Developing Robust Software for Advanced Applications is Difficult
+===Developing Robust Software for Advanced Applications is Difficult===
 Creating industrial-strength software solutions to support scientific investigations is time consuming and requires skills not usually found in the academic environment. NA-MIC has been successful at bringing in commercial software development expertise to help accomplish the Center's goals (GE, Kitware, Isomics) but these resources are routinely stretched well beyond the allocated budgets due to the many research directions of the Center's scientists. When considering biomedical computing projects, NIH should keep in mind the time consuming nature of such efforts, otherwise the resulting systems run a greater risk of being difficult to maintain, difficult to scale up, and incompatible across systems.
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 An excellent example of the level of effort needed for a successful, extensible, cross-platform product is the National Library of Medicine's Insight Toolkit (ITK). The organizational meeting for ITK was held in October 1999. Between October 1999 and October 2002, fifty developers contributed code from six prime contractors (GE, Kitware, Insightful, UNC, Utah, and UPenn) and four sub-contractors (BWH, UPenn, Pitt, and Columbia) to produce ITK Version 1.0. To date, over $13.5 million has been awarded by the NIH for the development, use, and expansion of ITK. That total includes 20, one-year contracts that were given to early adopters of ITK. When assessing the level of effort expended on ITK, it is important to consider that ITK's funding did not cover algorithm, graphical user interface, or visualization developments. ITK costs only funded the integration of existing methods into a common library. Developing end applications, involving user interfaces and visualizations tailored for clinical users, requires significant additional effort.
-Algorithm Development Needs to be Interactive and Not Sequential
+===Algorithm Development Needs to be Interactive and Not Sequential===
 In reviewing the last three years of the driving biological problem, schizophrenia, it is evident that tool development involved multiple interactions among members of Core 1 (Computer Scientists), 2 (Engineers), and 3 (Driving Biological Problem), at all stages of development, which led to the development of computational tools that were both more tailored to the specific applications needed by Core 3 members, as well as to the development of tools that were more optimized for general use. This interactive mode of tool development is in contrast to tool development that proceeds more sequentially, i.e., where one or several members of Core 1 and 3 met, and then Core 1 proceeded with what their understanding was of the problem and went off and developed a tool with very little further input from Core 3 until the tool was delivered. The latter approach often resulted in delays in receiving the tool, as there was less communication between Core 1 and Core 3 members in these instances, and often the tool did not really meet the specific needs of the application without further work. In the future, and based on this experience, NIH initiatives should emphasize the importance of encouraging a more "interactive" approach to tool development and to discouraging what is termed here as a more "sequential" approach to tool development. With a more interactive approach, progress can be more readily evaluated at each phase of tool development, and input and testing can be provided based on more communication among members of Core 1, 2, and 3. A more "interactive" model is also far more responsive to the needs of the driving biological problem, and also keeps the focus on the clinical application.
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 Focusing on interactions across core members will also likely facilitate breaking down the steep learning curve inherent in early interactions across cores members (see above).
-Funding
+===Funding===
 As mentioned above, there is a mismatch between the objectives set by NIH and the resources available to address them. This is evident in the driving biological problem being limited to three years, a time period when tools are just beginning to be applied in a meaningful manner to test specific hypotheses of the biomedical researchers. The time here needs to be the same for the tool development and application period. Moreover, additional cuts imposed over the last three years, combined with a "requirements creep", are problematic. In the future, increased interaction between Centers will require either additional resources or a change in the commitment of existing activities. Of further note, the more successful Centers are, the more there will be an increase in the number of scientists who will want to interact with scientists at the Centers, which will also require additional resources. NIH will thus need to allocate significant additional resources to Centers in order to fulfill the vision of a network of Centers of biomedical computing, at the center of an ever increasing network of biomedical scientific programs benefiting from their software and services.
 ==A list of publications and/or software tools produced by the Center==

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 This is the [[Media:2007 June NIH NCBC Review NA-MIC.pdf| Response submitted to NIH for NCBC Program Review of June 11, 2007 (pdf format)]].
-==Wiki Version of the Text==
+=Wiki Version of the Text=
-A copy of two parts of your most recent progress report: the summary section and the highlights section.
+==A copy of two parts of your most recent progress report: the summary section and the highlights section.==
-Summary
+===Summary===
 This Introduction section of the NA-MIC Progress Report provides a summary, and is excerpted here:
@@ Line 21: / Line 21: @@
-Highlights
+===Highlights===
 The Highlights Section of the Progress Report is excerpted here:
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 A brief statement - (one page per question, max) addressing each of the questions listed below.  These are the questions that we have been asked to address in our report.  Our goal in asking for this information is to be able to produce a report that reviews the program as a whole.  Your view, from the vantage point of the center you direct, is critical to our work.  In addition, your answers will provide us with more information that we can use in our discussion with program staff on June 11th.  We know that some of this information can be found on your websites, so in those cases a link to the information would be most helpful.
-To what extent does the vision and direction of the NCBC initiative promote biomedical computing?
+==1 To what extent does the vision and direction of the NCBC initiative promote biomedical computing?==
 The RFA for the creation of the NCBC program laid out a very explicit vision.
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 The participants in our center signed on for this project because they believe in the vision of developing a universal computing infrastructure for medical image computing. NA-MIC is creating an open source platform that embodies this vision for the field of medical image computing. We have settled on a very liberal open source license for our software platform. All the components of that platform, called the NA-MIC kit, are distributed under a BSD style license without restrictions on commercial use. Other centers have adopted different strategies to address the requirement for open source and to enable commercial use, as required in the original RFA; we believe the NA-MIC liberal license approach minimizes barriers to wide adoption and will maximize return on the NIH investment. The availability of software platforms commoditizes infrastructure for research and allows individual researchers to spend more time on their core research. Over time, this will promote biomedical computing by lowering the hurdle for scientists to use the technology.
-In what ways has the NCBC initiative advanced biomedical computing?
+==2 In what ways has the NCBC initiative advanced biomedical computing?==
 In assessing the impact of the NCBC initiative on biomedical computing, an important point to note is the short duration for which these Centers have been in existence: four of the NCBC's were funded less than three years ago (October 2004), and the other three less than two years ago (late 2005). Center efforts of this size and scope need significant time and effort to get organized and to synchronize the activities of all participants. This startup effort is where the primary focus of the Centers has been until now. There are early signs that some of the Centers are beginning to emerge from this phase of their evolution and turning toward activities aimed at the field at large. However, it will be several years before the full impact of this program will become visible.
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 **Over 50 NA-MIC related publications have been produced since the inception of the center.
-. Are the NCBCs interfacing appropriately?
+==3. Are the NCBCs interfacing appropriately?==
 Outreach across NCBCs is an effective use of resources. Initial efforts are ongoing and include cross-center use of software tools such as SimBios/SimTk actively using NA-MIC's VTK toolkit, and the use of the promising Software and Data Integration Working Group (SDIWG). In addition, NA-MIC has interactions with CCB and Simbios. NA-MIC also interfaces with a number of large-scale efforts which are not NCBC but are comparable in scale: BIRN, several national resource centers, and to some extent, with CaBIG. The NCBC's are thus interfacing appropriately.
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 Within the next few years there will be a need to increase NCBCs interfacing significantly. This will require either reallocation of resources or the allocation of new, additional resources. Due to the large variety of approaches adopted by the different centers it will likely be necessary to allocate significant amounts of time by senior leadership at the centers for identifying objectives of such efforts and by the engineering cores to actually execute the plans. A serious effort in this direction will probably require the allocation of multiple dedicated employees.
-. What new collaborations have been formed through the NCBC initiative?
+==4. What new collaborations have been formed through the NCBC initiative?==
 NA-MIC’s structure and organization has facilitated many, new collaborations. NA-MIC is a distributed center, bringing together mathematicians, computer scientists, software engineers, and clinicians from multiple sites. This distributed structure provides two types of new collaborations within NA-MIC: new collaborations between cores and new collaborations within cores. For between core collaborations, many of the algorithm and engineering core researchers had not collaborated previously with the researchers in either the first or second round of Driving Biological Projects (DBPs). Thus, the NCBC provides a unique opportunity for the algorithm and engineering core researchers to gain clinical insight and to adapt and tune their algorithms and tools to new clinical contexts.  Conversely, the DBPs have gained access to algorithms and tools that they previously did not have. Additionally, new collaborations among DBPs and Core 1 members is an important step in bringing together computer scientists and clinical researchers and we have been most successful here. Similarly, many of the algorithm core researchers and engineering core researchers had not previously collaborated. Thus, the NCBC exposed the researchers in the algorithm core to the tools and engineering practices of the engineering core and exposed the researchers in the engineering core to the computational techniques and data structures utilized by the algorithms core.  For within core collaborations, many of the researchers within the algorithm core had not previously collaborated. Through NA-MIC, these researchers have been able to cooperate and also amicably compete to address the issues brought forth by the DBPs.
@@ Line 192: / Line 192: @@
 * http://www.na-mic.org/Wiki/index.php/Engineering:Programming_Events
-. What new training opportunities have the centers provided?
+==5. What new training opportunities have the centers provided?==
 The requirement for all NCBC's to dedicate funds for training provides the opportunity to develop a targeted and deep portfolio of training resources. The unique perspective of providing these training opportunities and resources specifically targeted to a multi-disciplinary audience of basic and clinical biomedical scientists, computer scientists and medical imaging scientists is fostered by the NCBC Program. Traditional funding by NIH research grants results in allocation of all funds into the primary research; NIH training grants allocate funding for the support of trainees; the few education grants are restricted in budget and overhead thus severely limiting the quality and quantity of educational resources that can be offered. The NCBCs have created a new opportunity for experienced clinician scientists, computer scientists and medical image analysis experts affiliated with our centers to be supported to work on outreach activities.
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 Additional details of the NA-MIC Training effort are provided online at: http://www.na-mic.org/Wiki/index.php/Training:Main.
 . What changes could make the program more effective in the future?
 We believe that the program could be made more effective in the future by focused effort on three fronts: an increase in the national level visibility for the program, preservation of the local autonomy of the center leadership, and stability in the funding of the centers. Below we expand on each of these three suggestions.
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 As mentioned above, there is a mismatch between the objectives set by NIH and the resources available to address them. This is evident in the driving biological problem being limited to three years, a time period when tools are just beginning to be applied in a meaningful manner to test specific hypotheses of the biomedical researchers. The time here needs to be the same for the tool development and application period. Moreover, additional cuts imposed over the last three years, combined with a "requirements creep", are problematic. In the future, increased interaction between Centers will require either additional resources or a change in the commitment of existing activities. Of further note, the more successful Centers are, the more there will be an increase in the number of scientists who will want to interact with scientists at the Centers, which will also require additional resources. NIH will thus need to allocate significant additional resources to Centers in order to fulfill the vision of a network of Centers of biomedical computing, at the center of an ever increasing network of biomedical scientific programs benefiting from their software and services.
-A list of publications and/or software tools produced by the Center. If this information is provided in your progress report or is available on your website, a link will be sufficient.  We are especially interested in your assessment of the maturity of your software tools and the impact they are having on the scientific community.
+==A list of publications and/or software tools produced by the Center==
 NA-MIC Publications

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 ==Final Submission==
 This is the [[Media:2007 June NIH NCBC Review NA-MIC.pdf| Response submitted to NIH for NCBC Program Review of June 11, 2007 (pdf format)]].
-==Wiki Version of Text==
+==Wiki Version of the Text==
 A copy of two parts of your most recent progress report: the summary section and the highlights section.

← Older revision		Revision as of 01:02, 9 June 2007
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		+
		+	==Final Submission==
		+	This is the [[Media:2007 June NIH NCBC Review NA-MIC.pdf\| Response submitted to NIH for NCBC Program Review of June 11, 2007 (pdf format)]].
		+
		+	==Wiki Version of Text==

	A copy of two parts of your most recent progress report: the summary section and the highlights section.		A copy of two parts of your most recent progress report: the summary section and the highlights section.

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 =='''Q3:A list of publications and/or software tools produced by the Center.''' If this information is provided in your progress report or is available on your website, a link will be sufficient.  We are especially interested in your assessment of the maturity of your software tools and the impact they are having on the scientific community.==
 The Center has created and extended a number of software tools to handle some of the key problems in medical imaging analysis and to deliver these computational technologies via a suite of applications, toolkits, and infrastructure facilities. A summary description of these tools includes:
 * Slicer3 (application) - a application platform for deploying imaging technologies, newly architected with an execution model facilitating integration, work flow, and large scale computing. While Slicer3 is the newest addition to the NAMIC Kit, it is built on pre-existing, mature toolkits so that the application is relatively mature, and is already in use. Because Slicer3 supports plug-in modules, active development is proceeding to create and package various modules for dissemination to the NAMIC community.
 * ITK (toolkit) - a mature system for image analysis, registration and segmentation (initially created in 1999). ITK is in use worldwide for medical imaging research and development.
 * VTK (toolkit) - a mature system for visualization, graphics, volume rendering, and interaction (initially created in 1993). VTK is used worldwide for research, teaching and commercial development.
-* DART (computational infrastructure) - a key component of the NAMIC quality control process, DART is used to coordinate and report the software testing process. It was created in the first year of NAMIC and is in constant use, therefore a mature system.
+* DART (computational infrastructure) - a key component of the NA-MIC quality control process, DART is used to coordinate and report the software testing process. It was created in the first year of NA-MIC and is in constant use, therefore a mature system.
-* CMake/CTest/CPack (computational infrastructure) - CMake and CTest are relatively mature systems used to manage the building and testing of software across diverse computer platforms. CMake is used worldwide by some of the [http://lwn.net/Articles// world's largest open source systems such as KDE]. CPack, a recent addition to the NAMIC kit, is used to simplify the packaging and dissemination of software across platforms. Thus in NAMIC we can easily deploy our software across Windows, Linux, Unix, and Mac platforms.
+* CMake/CTest/CPack (computational infrastructure) - CMake and CTest are relatively mature systems used to manage the building and testing of software across diverse computer platforms. CMake is used worldwide by some of the [http://lwn.net/Articles// world's largest open source systems such as KDE]. CPack, a recent addition to the NAMIC kit, is used to simplify the packaging and dissemination of software across platforms. Thus in NA-MIC we can easily deploy our software across Windows, Linux, Unix, and Mac platforms.
 * Other tools (computational infrastructure) - Many other software tools are used to support the development of advanced imaging applications, and to assist with large scale computing, including
 ** Teem - image processing tools (mature)
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 ** GridWizard - an application scheduler aimed at allowing researchers to easily harness the power of large computational grids. It lets you run tens of thousands of commands simultaneously on multiple clusters of computers by typing a single command, without writing scripts. It can be used by itself, and is currently being integrated with Slicer3 and as part of a web-based portal environment. (http://www.na-mic.org/Wiki/index.php/Slicer3:Grid_Interface)
-These tools address key problems in imaging including segmentation, registration, visualization, and shape analysis; or provide facilities supporting researchers and developers who wish to create advanced software applications. One of key characteristics of NAMIC is that we treat the development of advanced medical image analysis software holistically; that is, the complete cycle of algorithm design, efficient impmentations, quality control and dissemination are needed to effectively address challenges provided by the driving biological problems. Examples of how these tools are being used include the following:
+These tools address key problems in imaging including segmentation, registration, visualization, and shape analysis; or provide facilities supporting researchers and developers who wish to create advanced software applications. One of key characteristics of NA-MIC is that we treat the development of advanced medical image analysis software holistically; that is, the complete cycle of algorithm design, efficient implementations, quality control and dissemination are needed to effectively address challenges provided by the driving biological problems. Examples of how these tools are being used include the following:
-(a) Segmentation: Here there are a variety of tools of varying degrees of maturity ranging from the EM Segmentor (a widely distributed, mature algorithm included in Slicer3 as an application plug-in) to more recent work on DTI segmentation based on directional flows which are Matlab and C++ based. Powerful mature tools such as Bayesian segmentation have been recently included in Slicer (and have been available in ITK for some time now) which can be combined with very recent work on the semi-automated segmentation of the DPFC done in collaboration with Core 3 researchers. Further, tools previously developed by NAMIC researchers which have had a wide distribution have been put into Slicer. For example, geometric based segmentation methods (some of which were included in packages marketed by GE) were tailored for cortical segmentation, and included in the Slicer, and in fact even improved with the inclusion of statistical based approaches.
+(a) Segmentation: Here there are a variety of tools of varying degrees of maturity ranging from the EM Segmentor (a widely distributed, mature algorithm included in Slicer3 as an application plug-in) to more recent work on DTI segmentation based on directional flows which are Matlab and C++ based. Powerful mature tools such as Bayesian segmentation have been recently included in Slicer (and have been available in ITK for some time now) which can be combined with very recent work on the semi-automated segmentation of the DPFC done in collaboration with Core 3 researchers. Further, tools previously developed by NA-MIC researchers which have had a wide distribution have been put into Slicer. For example, geometric based segmentation methods (some of which were included in packages marketed by GE) were tailored for cortical segmentation, and included in the Slicer, and in fact even improved with the inclusion of statistical based approaches.
 (b) Registration: Similar remarks can be made for registration in which we have a spectrum ranging from very mature methods to very recent ones which are still being tested. In particular, mature widely distributed methodologies for rigid registration are now included in ITK, as well as spline-based registration methodologies. These are well-tested methods which have been made accessible to the general imaging community. Newer methodologies such as those based on optimal transport for elastic registration are being included in ITK. NAMIC has also pushed for fast implementations of its algorithms to be used on cheap widely available platforms. Taking a cue from the game industry, some algorithms have been ported to GPUs (graphics cards) which are being employed now as computing devices. This has led to a speed-up of almost two orders of magnitude on some of the registration algorithms being tested.

← Older revision		Revision as of 18:27, 8 June 2007
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	As mentioned above, there is a mismatch between the objectives set by NIH and the resources available to address them. Moreover, additional cuts imposed over the last three years, combined with a "requirements creep", are problematic. In the future, increased interaction between Centers will require either additional resources or a change in the committment of existing activities. Of further note, the more successful Centers are, the more there will be an increase in the number of scientists who will want to interact with scientists at the Centers, which will also require additional resources. NIH will thus need to allocate significant additional resources to Centers in order to fulfill the vision of a network of Centers of biomedical computing, at the center of an ever increasing network of biomedical scientific programs benefiting from their software and services.		As mentioned above, there is a mismatch between the objectives set by NIH and the resources available to address them. Moreover, additional cuts imposed over the last three years, combined with a "requirements creep", are problematic. In the future, increased interaction between Centers will require either additional resources or a change in the committment of existing activities. Of further note, the more successful Centers are, the more there will be an increase in the number of scientists who will want to interact with scientists at the Centers, which will also require additional resources. NIH will thus need to allocate significant additional resources to Centers in order to fulfill the vision of a network of Centers of biomedical computing, at the center of an ever increasing network of biomedical scientific programs benefiting from their software and services.

−	=='''Q3:A list of publications and/or software tools produced by the Center.''' If this information is provided in your progress report or is available on your website, a link will be sufficient. We are especially interested in your assessment of the maturity of your software tools and the impact they are having on the scientific community.===	+	=='''Q3:A list of publications and/or software tools produced by the Center.''' If this information is provided in your progress report or is available on your website, a link will be sufficient. We are especially interested in your assessment of the maturity of your software tools and the impact they are having on the scientific community.==