NA-MIC National Alliance for Medical Image Computing Modeling Populations and Pathology Kayhan N. Batmanghelich PI: Polina Golland MIT.

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NA-MIC National Alliance for Medical Image Computing Modeling Populations and Pathology Kayhan N. Batmanghelich PI: Polina Golland MIT

National Alliance for Medical Image Computing 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)

National Alliance for Medical Image Computing Brain Connectivity Modeling Theoretical framework: –Joint inference across all connections New model: disease foci –Aggregate connectivity changes due to disease into information about regions

National Alliance for Medical Image Computing Results in a Schizophrenia Study R PCC R STG L STG Reduced connectivity in schizophrenia Increased connectivity in schizophrenia A P L R Detected RegionsAbnormal Connectivity Venkataraman MICCAI ‘12, submitted to IEEE TMI

National Alliance for Medical Image Computing Summary Connectivity differences in schizophrenia –Implicated regions and associated connections Venkataraman MICCAI ‘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

National Alliance for Medical Image Computing 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 left parotidbrainstemright parotid before registration after linear alignment after non-rigid deformation (final)

National Alliance for Medical Image Computing Local Data Influence in Segmentation Contour information in atlas-based segmentation –Application: left atrium segmentation Wachinger MICCAI ‘12 1. Contours2. Regions3. Region vote Image Label map Segmentation Spectral Label Fusion

National Alliance for Medical Image Computing Conclusions Generative modeling of populations –Population differences –Subject-specific analysis Applications to DBPs –Brain connectivity Venkataraman Schizophrenia Research ’12, MICCAI ’12, IEEE TMI ’12, IEEE TMI submitted –Anatomical segmentation (head-and-neck, left atrium) Wachinger MICCAI ’12