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Modeling Populations and Pathology

Modeling Populations and Pathology. Kayhan N. Batmanghelich PI: Polina Golland MIT. Modeling Populations and Pathology. Pathology deviates from normative atlases Our solution: Atlases for normal anatomy and function Explicit models of pathology Projects:

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Modeling Populations and Pathology

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  1. Modeling Populations and Pathology Kayhan N. Batmanghelich PI: PolinaGolland MIT

  2. Modeling Populations and Pathology • Pathology deviates from normative atlases • Our solution: • Atlases for normal anatomy and function • Explicit models of pathology • Projects: • Brain connectivity in clinical populations (HD) • Image segmentation in pathology • Anatomy segmentation for radiotherapy (head-and-neck) • Refined boundary finding (left atrium)

  3. Brain Connectivity Modeling • Theoretical framework: • Joint inference across all connections • New model: disease foci • Aggregate connectivity changes due to disease into information about regions

  4. Results in a Schizophrenia Study Detected Regions Abnormal Connectivity P L R STG L STG R PCC R A Reduced connectivity in schizophrenia Increased connectivity in schizophrenia Venkataraman MICCAI ‘12, submitted to IEEE TMI

  5. Summary • Connectivity differences in schizophrenia • Implicated regions and associated connections VenkataramanMICCAI ‘12, IEEE TMI ‘12, IEEE TMI submitted, Schizophrenia Research ’12 • This year: apply our algorithms to HD data • Close discussions with HD DBP (Hans Jonson) • Identified a subject set of HD patients and normal controls with fMRI and DWI data • Additional funding from CHDI Foundation

  6. Atlas-based Segmentation in the Presence of Pathology • Use atlas priors to segment anatomy around the tumor • Atlas methodology: label fusion • Application: head-and-neck before registration after linear alignment after non-rigid deformation (final) left parotid brainstem right parotid

  7. Local Data Influence in Segmentation • Contour information in atlas-based segmentation • Application: left atrium segmentation Spectral Label Fusion Image 1. Contours 2. Regions 3. Region vote Segmentation Label map Wachinger MICCAI ‘12

  8. Conclusions • Generative modeling of populations • Population differences • Subject-specific analysis • Applications to DBPs • Brain connectivity • VenkataramanSchizophrenia Research ’12, MICCAI ’12, IEEE TMI ’12, IEEE TMI submitted • Anatomical segmentation (head-and-neck, left atrium) • Wachinger MICCAI ’12

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