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EMSegmentation in Slicer 3 B. Davis, S. Barre, Y. Yuan, W. Schroeder, P. Golland, K. Pohl.

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Presentation on theme: "EMSegmentation in Slicer 3 B. Davis, S. Barre, Y. Yuan, W. Schroeder, P. Golland, K. Pohl."— Presentation transcript:

1 EMSegmentation in Slicer 3 B. Davis, S. Barre, Y. Yuan, W. Schroeder, P. Golland, K. Pohl

2 Overview Introduction Introduction EM Module Step-By-Step EM Module Step-By-Step Feedback & Discussion Feedback & Discussion Live Demo Live Demo

3 Motivation

4 Hierarchical Tree

5 Applications of EM Segmenter Subcortical Segmentation Psychiatry Neuroimaging Laboratory BWH, Harvard White Matter Lesion Center for Neurological Imaging BWH, Harvard

6 Goals Slicer2 Slicer3 Design automatic segmenter that Design automatic segmenter that is easy to use is easy to use adapts to variety of scenarios adapts to variety of scenarios works on large data sets works on large data sets is a research tool is a research tool

7 Overview Introduction Introduction EM Module Step-By-Step EM Module Step-By-Step Feedback & Discussion Feedback & Discussion Live Demo Live Demo

8 Parameter Set Atlas Tree Intensity Target Parameters Registration Run Wizard Interface Separates complex tasks into a sequence of simpler steps Checks user input before each transition Provides consistent access to help

9 Parameter Set Atlas Tree Intensity Target Parameters Registration Run Create new parameter set Apply/modify existing parameter set Parameter set defines segmentation scenario: Atlas, Images, Algorithm parameters Atlas, Images, Algorithm parameters

10 Parameter Set Atlas Tree Intensity Target Parameters Registration Run Defines a hierarchy of anatomical structures

11 Parameter Set Atlas Tree Intensity Target Parameters Registration Run Assign atlas to anatomical structures white mattercsf grey matter background

12 Parameter Set Atlas Tree Intensity Target Parameters Registration Run Choose input channels T1 T2

13 Parameter Set Atlas Tree Intensity Target Parameters Registration Run Define intensity distribution for each structure

14 Parameter Set Atlas Tree Intensity Target Parameters Registration Run Specify node-based segmentation parameters Influence of Influence of Input channels Input channels Atlas Atlas Smoothing Smoothing Relative weight to other structures Relative weight to other structures Stopping conditions Stopping conditions

15 Parameter Set Atlas Tree Intensity Target Parameters Registration Run Specify atlas-to-input channel registration white mattercsf grey matter background T1 T2

16 Parameter Set Atlas Tree Intensity Target Parameters Registration Run Segment input channels using parameters

17 Pipeline 2 Atlas Alignment 3 EM Segmentation 1 Intensity Normalization

18 Observed Data (ROI) EM Image Prior HierarchyLabelmap EM Segmenter

19 Level 1 Prior Information IMAGE BGICC CSFGMWM

20 Level 2 IMAGE ICC Current Parameter CSFGMWM ROI

21 Example Tree

22

23 Overview Introduction Introduction EM Module Step-By-Step EM Module Step-By-Step Feedback & Discussion Feedback & Discussion Live Demo Live Demo

24 Resouces Slicer3 EMSegment Wiki page: http://wiki.na-mic.org/Wiki/index.php/Slicer3:EM Slicer3 EMSegment Wiki page: http://wiki.na-mic.org/Wiki/index.php/Slicer3:EM http://wiki.na-mic.org/Wiki/index.php/Slicer3:EM Project Description Project Description Steps in EMSegment Workflow Steps in EMSegment Workflow Future Work Future Work Implementation Details Implementation Details EMSegment Tutorial EMSegment Tutorial Slicer2 Material: Slicer2 Material: Tutorial: http://wiki.na-mic.org/Wiki/index.php/ Slicer:Workshops:User_Training_101 Tutorial: http://wiki.na-mic.org/Wiki/index.php/ Slicer:Workshops:User_Training_101 Publications Publications K.M. Pohl, S. Bouix, R. Kikinis, W.E.L. Grimson, Anatomical Guided Segmentation with Non-Stationary Tissue Class Distributions in an Expectation-Maximization Framework, In Proc. ISBI 2004, pp. 81-84,2004 K.M. Pohl, S. Bouix, R. Kikinis, W.E.L. Grimson, Anatomical Guided Segmentation with Non-Stationary Tissue Class Distributions in an Expectation-Maximization Framework, In Proc. ISBI 2004, pp. 81-84,2004 K.M. Pohl, S. Bouix, M.E. Shenton, W.E.L. Grimson, R. Kikinis, Automatic Segmentation Using Non-Rigid Registratio, short communications of MICCAI 2005 K.M. Pohl, S. Bouix, M.E. Shenton, W.E.L. Grimson, R. Kikinis, Automatic Segmentation Using Non-Rigid Registratio, short communications of MICCAI 2005

25 Feedback & Discussion Priorities for future development Priorities for future development Class overview panel Class overview panel Graphical Display Graphical Display Controlled vocabulary Controlled vocabulary Library of Templates Library of Templates One-Step-Segmentation One-Step-Segmentation

26 Acknowledgements Steve Pieper Steve Pieper Alex Yarmarkovich Alex Yarmarkovich Wendy Plesniak Wendy Plesniak Slicer developer community Slicer developer community Psychiatry Neuroimaging Laboratory Psychiatry Neuroimaging Laboratory NAMIC NAMIC

27 Acknowledgements Kitware Developer Kitware Developer

28 Overview Introduction Introduction EM Module Step-By-Step EM Module Step-By-Step Feedback & Discussion Feedback & Discussion Live Demo Live Demo

29 Editing the Tree CorticalSubcorticalLevel 3:


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