NA-MICNational Alliance for Medical Image Computing http://na-mic.org

Engineering a Segmentation Framework

Marcel Prastawa

National Alliance for Medical Image Computing http://na-mic.org

Need for Segmentation Applications

• Longitudinal analysis of growth• Preprocessing for shape analysis• Detect pathology

Fully automatic, reproducibleAllow fast prototypingExecute on hundreds of datasets

National Alliance for Medical Image Computing http://na-mic.org

Our Method: Atlas-based Brain Segmentation

T1 T2 Tissue Cortex

National Alliance for Medical Image Computing http://na-mic.org

Quick Demo

National Alliance for Medical Image Computing http://na-mic.org

Engineering ComponentsFiltering

Inhomogeneity Correction

Affine Registration

Deformable Registration

Segmentation

Statistics

Pathology

Atlas

National Alliance for Medical Image Computing http://na-mic.org

Shared Components (EMSegment)

• Filtering• Registration• Inhomogeneity Correction• Statistics

• Atlas• Pathology

National Alliance for Medical Image Computing http://na-mic.org

Future Components

• New modality / information– DTI– Vessels / MRA

• Pathology model– Tumor biomechanical model– Lesion model

• New classifiers

National Alliance for Medical Image Computing http://na-mic.org

GUI vs Batch Mode

• GUI for prototyping• Command line for batch processing:

– Use automatically generated XML file– Different input images, same parameters– Python or shell scripts

National Alliance for Medical Image Computing http://na-mic.org

Sample XML Input [1/2]<?xml version="1.0"?><!DOCTYPE SEGMENTATION-PARAMETERS><SEGMENTATION-PARAMETERS><SUFFIX>EMS</SUFFIX><ATLAS-DIRECTORY>/scratch/prastawa/atlases/adult-atlas</ATLAS-

DIRECTORY><ATLAS-ORIENTATION>RAI</ATLAS-ORIENTATION><OUTPUT-DIRECTORY>/scratch/prastawa/test/out</OUTPUT-DIRECTORY><OUTPUT-FORMAT>GIPL</OUTPUT-FORMAT><IMAGE> <FILE>/scratch/prastawa/test/T1_Orig.nrrd</FILE> <ORIENTATION>ASR</ORIENTATION></IMAGE><IMAGE> <FILE>/scratch/prastawa/test/T2_Orig.nrrd</FILE> <ORIENTATION>ASR</ORIENTATION></IMAGE>...

National Alliance for Medical Image Computing http://na-mic.org

Sample XML Input [2/2]...<FILTER-ITERATIONS>1</FILTER-ITERATIONS><FILTER-TIME-STEP>0.01</FILTER-TIME-STEP><FILTER-METHOD>Curvature flow</FILTER-METHOD><MAX-BIAS-DEGREE>4</MAX-BIAS-DEGREE><PRIOR-1>1.2</PRIOR-1><PRIOR-2>1</PRIOR-2><PRIOR-3>0.7</PRIOR-3><PRIOR-4>1</PRIOR-4><DO-ATLAS-WARP>1</DO-ATLAS-WARP><ATLAS-WARP-GRID-X>5</ATLAS-WARP-GRID-X><ATLAS-WARP-GRID-Y>5</ATLAS-WARP-GRID-Y><ATLAS-WARP-GRID-Z>5</ATLAS-WARP-GRID-Z></SEGMENTATION-PARAMETERS>

National Alliance for Medical Image Computing http://na-mic.org

Smart Execution

• Fast prototyping by storing results at different stages

• Examples:– Store registration transforms– Store estimated intensity distributions

• Write new results when input parameters changed

National Alliance for Medical Image Computing http://na-mic.org

Tumor Segmentation

T1 3DT2

T1 3DT2

National Alliance for Medical Image Computing http://na-mic.org

Neonate Segmentation

T1 T2 3D

T1 T2 3D

National Alliance for Medical Image Computing http://na-mic.org

Lupus Lesion Segmentation

T2 FLAIR

3D

National Alliance for Medical Image Computing http://na-mic.org

Discussion

• Integrated system for registration, bias correction, segmentation

• Implemented using ITK classes• Cross-platform: Linux, Windows, Solaris• Smart execution: stored states• Shared components• Slicer integration?