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Core 1 & Core 3 Projects. Existing projects: Core 1 & 3. Harvard and University of North Carolina Shape analysis of caudate Automatic Segmentation of corpus callosum based on Diffusion Fiber Tracking Model ITK SNAP : Level set semiautomatic segmentation tool

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Core 1 & Core 3 Projects

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Core 1 core 3 projects

Core 1 & Core 3 Projects


Existing projects core 1 3

Existing projects: Core 1 & 3

Harvard and University of North Carolina

Shapeanalysis of caudate

Automatic Segmentation of corpus callosum based on Diffusion Fiber Tracking Model

ITK SNAP: Level set semiautomatic segmentation tool

Statistical analysis of DTI measures along white matter fibers

[Participants: UNC: Isabelle Corouge, Martin Styner, Guido Gerig

PNL: Sylvain Bouix, Marek Kubicki, James Levitt,

Marc Niethammer, Martha Shenton]


Existing projects core 1 31

Existing projects: Core 1 & 3

Harvard and Massachusetts Institute of Technology

Diffusion measures along cingulum bundle fiber tracts

Clustering of specific fiber tracts based on location & regions they connect

Atlas of human brain white matter fiber bundles using automatic population based clustering

FA/Trace measures of corpus callosum and anterior commissure

[Participants: MIT: Lauren O’Donnell, CF Westin, Scott Hoge, Raul San Jose, Eric Grimson

PNL: Marc Niethammer, Sylvain Bouix, Marek Kubicki, Mark Dreusicke, Martha Shenton]

Brain tissue classification and subparcellation of brain structures

[Participants: MIT: Kilian Pohl, Sandy Wells, Eric Grimson

PNL: Sylvain Bouix, Motaki Nakamura, Min-Seong Koo, Martha Shenton]


Existing projects core 1 32

Existing projects: Core 1 & 3

Harvard and Georgia Tech

Semiautomatic segmentation and parcellation of basal ganglia

[Participants: GTech: Ramsey Al-Hakim,

Delphine Nain, Allen Tannenbaum

PNL: Sylvain Bouix, James Levitt, Marc Niethammer, Martha Shenton]


Existing projects core 1 33

Existing projects: Core 1 & 3

UCI and Georgia Tech

Semiautomatic segmentation and parcellation of cortical and subcortical areas

[Participants: GTech: Ramsey Al-Hakim, Delphine Nain, Allen Tannenbaum

UCI: Jim Fallon, Vid Petrovic, Martina Panzenboeck]


Existing projects core 1 34

Existing projects: Core 1 & 3

UCI and UNC

Automated DTI tractography and atlas development


Existing projects core 1 35

Existing projects: Core 1 & 3

Harvard and Utah

New anisotropic measures for white matter diffusion

[Participants: Utah: Tom Fletcher, Ross Whitaker

PNL: Sylvain Bouix, Marek Kubicki,

Martha Shenton]


Quantitative fiber tract analysis uci and unc

Quantitative Fiber Tract AnalysisUCI and UNC

  • For clinical studies

    • UNC: neonatal studies in autism, SZ

  • For neuroanatomy and connectivity exploration

  • NAMIC collaboration with UC Irvine (Jim Fallon)

  • NAMIC collaboration with Shenton/Marek

  • UNC: Krabbe’s disease

  • UNC: Neonatal & Autism Studies

  • UNC: Healthy Aging Study

[Fallon]


Rule based brain segmentation

Rule-Based Brain Segmentation

  • We are developing common tools needed for rule-based semi-automatic segmentation algorithms

  • 3 Prototype programs have been created to segment different brain structures based on neurological rules and minimal user input


Common tool thumb extraction uci and gatech

Common tool: “Thumb” Extraction: UCI and GaTech

  • Extraction of “thumbs” using an intensity-based energy minimized using Fast Marching methods

  • Applications to rule-based algorithms

  • Currently being ported from Matlab to VTK

“Thumb”

John Melonakos (GaTech), Jim Fallon (UCI)


Core 1 core 3 projects

Example: Segmentation of Putamen: UCI/Ga Tech

MRI image of striatum showing the putamen.

Gradient of the image showing edge information.

  • The user specifies several points on

    the border of the Putamen on each slice.

  • The algorithm finds the lowest cost

    outline of the structure based on edge

    information in the image.

  • A 3D model is created for analysis

Shawn Lankton (GaTech), Jim Fallon (UCI)


Example rule based segmentation of the striatum in slicer harvard gatech

Example: Rule Based Segmentation of the Striatum in Slicer: Harvard/GaTech

  • Begin with manually segmented label of total striatum

  • Manually input most superior/dorsal point on putamen and anterior commissure; striatum is delineated automatically based on rules of Dr. James Levitt.

Most superior/dorsal point on putamen

Anterior commissure

Ramsey Al-Hakim (GaTech), James Levitt (SPL)


Example path of interest analysis dartmouth mgh isomics

Example: Path-of-interest analysis (Dartmouth/MGH/Isomics)

• Path-of-interestreconstruction

•Dartmouth DTI data

•Slicer visualization

http://www.na-mic.org/Wiki/index.php/Progress_Report:DTI_Path_of_interest_analysis

Saykin (Dartmouth), West (Dartmouth), Snyder (MGH), Tuch (MGH), Pieper (Isomics)


Example rule based segmentation of the striatum in slicer harvard gatech1

Pre Caudate

Post Caudate

Post Putamen

Nucleus Accumbens

Pre Putamen

Example: Rule Based Segmentation of the Striatum in Slicer: Harvard/GaTech

Anterior/Superior View of Delineated Striatum

Automatically marked label (blue lines input by user to designate superior/dorsal point on putamen)

Ramsey Al-Hakim (GaTech), James Levitt (SPL)


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