2007 Annual Scientific Report

Back to 2007_Progress_Report

For reference:

• 2006 Annual Scientific Report, 2006 Followup Questions and Answers.
• 2005 Annual Scientific Report

2. Four Main Themes

This year's activities focus on four main themes: Diffusion Image Analysis, Structural Analysis, Functional MRI Analysis, and the NA-MIC Kit. Each of the following sections begins with an overview of the theme, provides a progress update and list of key investigators, and concludes with a set of links to additional information for individual projects in that theme.

These thematic activities involve scientists from each of the 7 NA-MIC cores (Appendix).

• Core 1 Algorithms-Ross Whitaker PI
• Core 2 Engineering-Will Schroeder PI
• Core 3 DBP1-Martha Shenton PI / DBP2-Andy Saykin PI / DBP3-Steven Potkin PI
• Core 4 Service-Will Schroeder PI
• Core 5 Training-Randy Gollub PI
• Core 6 Dissemination-Tina Kapur Co-PI; Steve Pieper Co-PI
• Core 7 Leadership-Ron Kikinis

2.1 Diffusion Image Analysis Theme (Marek Kubicki, Guido Gerig)

Key Investigators

• BWH: Martha Shenton, Marek Kubicki, Marc Niethammer, Sylvain Bouix, Katharina Quintus, Mark Dreusicke, Carl-Fredrik Westin, Raul San Jose, Gordon Kindlmann, Doug Markant
• Harvard/MGH: Bruce Fischl, Denis Jen, David Kennedy
• MIT: Lauren O'Donnell
• UCI: James Fallon, Martina Panzenboeck
• UNC: Guido Gerig, Isabelle Corouge, Casey Goodlett, Martin Styner
• Utah: Tom Fletcher, Ross Whitaker, Saurav Basu
• Georgia Tech: Eric Pichon, John Melonakos, Xavier LeFaucheur, Allen Tannenbaum
• Dartmouth: John West, Andrew Saykin, Laura Flashman, Paul Wang, Heather Pixley, Robert Roth
• Isomics: Steve Pieper

Additional Information

For details of each of the projects in this theme, please see NA-MIC Projects on Diffusion Image Analysis.

2.2 Structural Analysis Theme (Allen Tannenbaum, Martin Styner)

Progress

Shape Driven Segmentation

The characterization of local variations specific to a shape population is an important problem in medical imaging since a given disease usually only effects a portion of an organ’s surface. In particular, one of the driving biological projects that motivates our work is the study of schizophrenia. Yet the clinical study of schizophrenia is only now beginning to take concrete form, primarily because neuroimaging techniques are finally providing a sufficiently detailed picture of the structure of the living brain and tracking the way the brain functions in controlled experimental settings. One important aspect of such an analysis of schizophrenia is the segmentation and shape analysis of selected brain structures, such as the hippocampus or the caudate nucleus, in order to find differences between groups of healthy and diseased patients. An automated segmentation of such structures must therefore be highly accurate and include high frequency variations in the surface. Since shape representation is a key component of the segmentation, it must be rich enough to express shape variations at various frequency levels, from low harmonics to sharp edges. Additionally, a shape representation that encodes variations at multiple scales can be useful in itself as a rich feature set for shape analysis and classification.

Medical object segmentation with deformable models and statistical shape modeling may be combined to obtain a more robust and accurate segmentation. To address this issue, a decomposable shape representation targeted to the population seems natural, where the shape parameters are separated into groups that describe independent global and/or local biological variations in the population, and a prior induced over each group explicitly encodes these variations. Wavelet basis functions are useful for such a representation since they range from functions with global support to functions localized both in frequency and space, so that their coefficients can be used both as global and local shape descriptors, unlike Fourier basis functions or principal components over landmarks which are global shape descriptors. Our work presents three novel contributions for shape representation, multiscale prior probability estimation and segmentation.

Key Investigators

• MIT: Kilian Pohl, Sandy Wells, Eric Grimson
• UNC: Martin Styner, Ipek Oguz, Guido Gerig
• Utah: Ross Whitaker, Suyash Awate, Tolga Tasdizen, Tom Fletcher, Joshua Cates, Miriah Meyer
• GaTech: Allen Tannenbaum, John Melonakos, Tauseef ur Rehman, Shawn Lankton, Ramsey Al-Hakim, Eric Pichon, Delphine Nain, Oleg Michailovich, Yogesh Rathi, James Malcolm
• Steve Pieper, Bill Lorensen, Luis Ibanez, Karthik Krishnan, Michael J. Pan, Jagadeeswaran Rajendiran, Jim Miller, Karthik Krishnan, Luis Ibanez
• Harvard PNL: Sylvain Bouix, Motoaki Nakamura, Min-Seong Koo, Martha Shenton, Marc Niethammer, Jim Levitt
• Dartmouth: Andrew Saykin
• UCI: James Fallon

Additional Information

For details of each of the projects in this theme, please see NA-MIC Projects on Structural Image Analysis.

2.3 Functional MRI Analysis Theme (Polina Golland, Andy Saykin)

Path Analysis?

2.4 NA-MIC Kit Theme (Will Schroeder)

Key Investigators

• GE: Bill Lorensen, Jim Miller, Xiaodong Tao, Dan Blezek
• Isomics: Steve Pieper, Alex Yarmarkovich
• Kitware: Will Schroeder, Luis Ibanez, Karthik Krishnan, Andy Cedilnik, Sebastien Barre, Mathieu Malaterre
• UCLA: Mike Pan, Jagadeeswaran Rajendiran
• UCSD: Neil Jones, Jeffrey Grethe
• Harvard: Nicole Aucoin, Katie Hayes, Wendy Plesniak, Mike Halle, Gordon Kindlmann, Raul San Jose Estepar, Haiying Liu, Ron Kikinis
• MIT: Lauren O'Donnell, Kilian Pohl

Additional Information

For details of each of the projects in this theme, please see NA-MIC Kit Projects.

3. Highlights (Will Schroeder)

• Slicer3

• EM Segmenter (http://wiki.na-mic.org/Wiki/index.php/Slicer3:EM)
  

We constructed a module that integrates the EMSegment algorithm---an automatic segmentation algorithm for medical images---into the Slicer3 platform. The project was a joint effort between the NAMIC engineering, algorithms, and biological problem cores. As in Slicer 2, the user is able to adjust the algorithm to a variety of imaging protocols as well as anatomical structures. However, the configuration of the algorithm is greatly simplified in Slicer 3 as the user is guided by a new wizard-style workflow interface.
A tutorial session for the EMSegment module was given at the January 2007 NAMIC all-hands meeting (notes and data available online athttp://wiki.na-mic.org/Wiki/index.php/Slicer3:EM). The module is available with the beta release of Slicer3. Future work includes testing, validation, and the integration of data preprocessing steps into the EMSegment module.

• As we published for the first time an open-source framework to do shape analysis in this NAMIC year, I think this is a highlight. It has been downloaded many times since the first online publication (around October 06) and it now used by several image analysis groups (not yet by the clinical researchers, we still need to package it nicely into Slicer v3). I updated our shape analysis page last week. The webpage with the information is here http://www.na-mic.org/Wiki/index.php/Algorithm:UNC:Shape_Analysis.

• Highlights [Algorithmic Development and Software Transfer at Georgia Tech]:
  • The spherical based wavelet shape analysis package has been put into ITK, and in the next few months the multiscale segmentation work will be incorporated as well. We then intend to import this menu of algorithmsin to 3D Slicer. All of our algorithms are open source, and are intended to be user friendly to give them the widest possible accessibility.
  • We have implemented a very fast method for the optimal transport approach to elastic image registration. This will be made available via

ITK in the next year.

• • Our tool for the semi-automated segmentation of DPFC areas in coronal sections of from brain MRI data developed in collaboration with our Core 3 colleague Dr. James Fallon is in Slicer 2. This will be ported to Slicer 3 in the next year as well.
  • ITK code has been for the conformal flattening procedure has been ported to an ITK filter and is in the NAMIC Sandbox.

• Dissemination-
  • Papers- Number of algorithms papers (count the number of NAMIC MICCAI papers accepted - it was significant). In fact, all 3 DTI papers presented at MICCAI last year were NAMIC associated.
  • DissemnHighlight a tutorial or other training event. E.g. attendance at the UNC-DTI workshop was good and there will be another such workshop at HBM

5.NA-MIC Timeline (Ross Whitaker)

This section provides a table of NAMIC timelines from the original proposal that graphically depicts completed tasks/goals in years 1, 2, and 3 and tasks/goals to be completed in years 4-5. Changes to the original timelines have also been described.

2007 Scientific Report Timeline

6. EAB Report

The NA-MIC External Advisory Board (EAB), chaired by Prof. Chris Johnson of the University of Utah, met at the annual All-Hands Meeting. After individual presentations by NA-MIC investigators and open as well as closed-door EAB discussion, the Board provided its independent expert assessment of the Center (Appendix 2).

Logistics

Schedule and process for preparation of this report

• March 30 - Assign section/theme leads (Ron). Last year: introduction (marty), structural analysis (allen, martin), dti (guido, marty/marek), fmri (polina, andy), namic kit(bill), timeline (ross), highlights (will), impact (bill).
• April 7,10 - tcons with Marty, Ross, Will, Tina to finalize the layout, process, and timeline of report.
• April 13 - update projects list using last year's NA-MIC_Collaborations and projects pursued at the half week in SLC. Remind investigators to update individual pages. (Tina)
• April 23- complete project description pages in updated list: NA-MIC_Collaborations (all project owners).
• April 30 - complete section summaries, introduction, highlights, impact, timeline (owners of these topics)
• May 3 - submit wiki report to NA-MIC editor, Ann (Tina)
• May 17 - submit Edited report to Rachana (Ann)
• May 31 - ship final package to NIH (Rachana)

Guidelines from NIH Program Officer

The following guidelines were provided by Grace Peng, NA-MIC program officer, in Feb 2006.

The key is to synthesize all the individual elements into bigger picture stories that really speak of each area’s impact to the community.

The specialized scientific report should have the following format:

1. Introductory page describing the new grouping of NAMIC project themes.
2. A description of progress in each NAMIC project theme (not to exceed 2 pages each), tying together relevant activities from participating subcomponents and referencing cores in parentheses.
3. A table of NAMIC timelines (from original proposal), graphically depicting completed tasks/goals in years 1,2, and 3 and tasks/goals to be completed in years 4-5. Changes to the original timelines should be described.
4. A description of 3 highlights selected from all NAMIC projects to showcase NAMIC.
5. A discussion of NAMIC’s impact and value to the biocomputing community this year.