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Model-Based Strategies for Biomedical Image Analysis

Model-Based Strategies for Biomedical Image Analysis. James S. Duncan Image Processing and Analysis Group Departments of Biomedical Engineering, Diagnostic Radiology and Electrical Engineering Yale University. Experiment – Functional Subnetworks. Green = Amygdala Purple = FFG Red= STS

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Model-Based Strategies for Biomedical Image Analysis

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  1. Model-Based Strategies for Biomedical Image Analysis James S. Duncan Image Processing and Analysis Group Departments of Biomedical Engineering, Diagnostic Radiology and Electrical Engineering Yale University

  2. Experiment –Functional Subnetworks Green = Amygdala Purple = FFG Red= STS Pink=IFG • Performed classification on sample of 5 normal child subjects: • Look at average probability within atlas ROI and subgroup of interest • In agreement with proposed subgroups of the “social brain” green purp red pink Subgroup probability averaged over ROI

  3. The Tracking Algorithm (L.Liang, et al., MICCAI 2011) Anchored Brownian Motion Image Sequences (in Selected Regions) Select (manually) regions away from Golgi apparatus and nucleus (1) Find local maxima LoG filter, histogram thresholding (2) Fit Gaussian models (point spread func.) Particle Detection Establish the links among detected particles using a multiple hypothesis based method Trajectory Estimation t

  4. Strain from MRI(Shape-Tracking:Sinusas, et al, AJP, 2003) Normal Canine Heart 1 Hour Post- LAD Occlusion Infarct region strains for N=6 dogs

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