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NA-MIC Highlights: A Core 1 Perspective. Ross Whitaker University of Utah. National Alliance for Biomedical Image Computing. Algorithms Productivity. Things we have hardly thought about. Clinical/ Biomedical Science. Applied Methodology Validation/Evaluation. New methods.

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Na mic highlights a core 1 perspective

NA-MIC Highlights:A Core 1 Perspective

Ross Whitaker

University of Utah

National Alliance for Biomedical Image Computing

Algorithms productivity
Algorithms Productivity

Things we have hardly thought about




Applied Methodology


New methods

Things we have

not yet published






Algorithms productivity1
Algorithms Productivity

Adopted by unaffiliated groups

One-off prototypes

Proof of concept

Reusable (by friends)

Software and tools

Algorithms productivity2
Algorithms Productivity



The real goal

Diffusion mri in schizophrenia
Diffusion MRI in Schizophrenia

Lee et al, “ Increased diffusivity in superior temporal gyrus in patients with schizophrenia: a Diffusion Tensor Imaging study”, Schiz. Res. 2009.

Tissue classification and hand segmentation of STG

Group differences and correlations with DTI measures

Dti in neurodevelopment
DTI in Neurodevelopment

Goodlett et. al, “Group analysis of DTI fi ber tract statistics with application to neurodevelopment”, Neuroimage, 2009.

Longitudinal studies of dti
Longitudinal Studies of DTI

Gouttard et. al, “Constrained Data Decomposition and

Regression for Analyzing Healthy Aging from

Fiber Tract Diffusion Properties”, MICCAI, 2009.

Atlas based alignment and tract identification

Localized statistics on longitudinal models

Atlases and segmentation for scientific studies
Atlases and Segmentation for Scientific Studies

Leemput et al., “Automated Segmentation of Hippocampal Subfields From Ultra-High Resolution In Vivo MRI”, Hippocampus, 2009.

Bayesian Image analysis for parcellation of the hippocampus

New technologies for atlases segmentation
New Technologies for Atlases/Segmentation

Riklin Raviv et al., “Joint Segmentation of Image Ensembles via Latent Atlases”, MICCAI 2009

Gerber et al., “On The Manifold Structure of the Space of Brain Images”, MICCAI 2009

Bootstrapping atlas with very little prior data

Discovering/utilizing underlying parameters of large image databases

New technologies for segmentation
New Technologies for Segmentation

Karasev et al., “Conformal Geometric Flows for Surface Segmentation”, 2010

Prastawa et al., “Stastical analysis and segmentation with pathology”, 2010

Applications of statistical atlases with allowances for outliers

Region specification by geometric flows on surfaces

Shape analysis in schizophrenia
Shape Analysis in Schizophrenia

Levitt et al., “Shape abnormalities of caudate nucleus in schizotypal personality disorder”, Schiz. Res., 2009.

Global and local caudate shape abnormalities in male and female SPD

Correspondence and shape multimodal cortex
Correspondence and Shape: Multimodal, Cortex

Oguz et al., “Cortical correspondence with probabilistic fiberconnectivity”, IPMI, 2009.

Combine shape and connectivity for group correspondence

More consistent alignment of cortex relative to state of the art

Shape and regression development
Shape and Regression/Development

Datar et al., “Particle Based Shape Regression of Open Surfaces with Applications to Developmental Neuroimaging”, MICCAI, 2009.

Correspondence incorporate an underlying developmental model

Where we are headed
Where We Are Headed



New Ideas

Biomedical/Clinical Science

Stay tuned
Stay Tuned!

  • Investigators:

    • P. Golland – MIT

    • A. Tannenbaum – Georgia Tech

    • M. Stynder – UNC

    • G. Gerig – Utah