Level-Set Evolution with Level-Set Evolution with Region Competition:Region Competition:Automatic 3-D Segmentation of Automatic 3-D Segmentation of Brain TumorsBrain Tumors

1Sean Ho, 2Elizabeth Bullitt, and 1;3Guido Gerig

1Department of Computer Science,2Department of Surgery,3Department of PsychiatryUniversity of North Carolina, Chapel Hill, NC, USA

Supported by NIH-NCI R01 CA67812.Partially supported by NIH-NCI P01 CA47982.

Tumor segmentationTumor segmentation

Focusing on Focusing on meningiomas and meningiomas and glioblastomasglioblastomas

Glioblastomas have a Glioblastomas have a ring enhancement that ring enhancement that makes segmentation makes segmentation toughtough

Overview of the Overview of the procedureprocedure

1.1. Multiparameter MR image dataMultiparameter MR image data2.2. Fuzzy voxel-based segmentationFuzzy voxel-based segmentation3.3. Level-set snake driven by:Level-set snake driven by:

1.1. Region competitionRegion competition2.2. Smoothness constraintsSmoothness constraints

Can use alone for enhancing tumorsCan use alone for enhancing tumors Or as part of the Or as part of the

tumor/tissue/vasculature tumor/tissue/vasculature segmentationsegmentation

Multiparameter MR Multiparameter MR imagesimages

T1GAD-T1 registered difference imageT1GAD-T1 registered difference image T2 available but not used in this workT2 available but not used in this work

=-

Probability map of enhancing Probability map of enhancing tissuetissue

T1GAD-T1 registered difference imageT1GAD-T1 registered difference image Mixture-model histogram fit:Mixture-model histogram fit:

Gaussian for the backgroundGaussian for the background Gamma function for the contrast agent Gamma function for the contrast agent

uptakeuptake

Region competition Region competition snakesnake

Image force: modulate propagation by Image force: modulate propagation by signed inside/outside forcesigned inside/outside force

Smoothness constraint:Smoothness constraint: Mean curvature flowMean curvature flow Gaussian smoothing of the implicit Gaussian smoothing of the implicit

functionfunction

Enhancement => image Enhancement => image forceforce

Live demoLive demo

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20 300

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ResultsResults

Very challenging segmentation problem, Very challenging segmentation problem, even for expert manual segmentation:even for expert manual segmentation: Complex tumor geometryComplex tumor geometry Complex greylevel appearanceComplex greylevel appearance Nearby enhancing structures (e.g. vessels, Nearby enhancing structures (e.g. vessels,

bone)bone) Some examples:Some examples:

ValidationValidation

Compared against expert human raterCompared against expert human rater Validation with 2Validation with 2ndnd human rater in human rater in

progressprogress More tumor datasets on the wayMore tumor datasets on the way

DatasetDataset VolumVolume e OverlaOverlapp

HausdorHausdorff ff (mm)(mm)

In In (mm(mm))

Out Out (mm(mm))

AveragAverage e (mm)(mm)

Tumor02Tumor0200

93.2%93.2% 6.926.92 0.470.47 1.071.07 0.590.59

Tumor02Tumor0222

89.5%89.5% 13.0213.02 0.490.49 4.134.13 1.491.49

Tumor02Tumor0255

84.7%84.7% 10.7310.73 0.830.83 1.071.07 0.850.85

Integrating in the “Big Integrating in the “Big Picture”Picture”

Modify Modify atlasatlas with subject specific with subject specific pathologypathology Probability map of enhancing tissueProbability map of enhancing tissue Region-competition snakeRegion-competition snake

Smoothness constraintsSmoothness constraints

EM tissue EM tissue classificationclassification (previous talk): (previous talk): Using spatial priorUsing spatial prior Additional tumor and edema classesAdditional tumor and edema classes Bias field inhomogeneity compensationBias field inhomogeneity compensation

Result: Combined Result: Combined tumortumor and and tissuetissue segmentation (gm, wm, csf, edema)segmentation (gm, wm, csf, edema)

The “Big Picture”, cont.The “Big Picture”, cont.

Tumor segmentation registered Tumor segmentation registered with segmentation of with segmentation of vasculaturevasculature:: We also have MRA imagesWe also have MRA images Vessel extraction softwareVessel extraction software

Free software Free software downloadsdownloads midag.cs.unc.edumidag.cs.unc.edu SNAPSNAP (prototype): (prototype):

3D level-set evolution3D level-set evolution Preprocessing pipeline Preprocessing pipeline

and manual editingand manual editing VALMET (prototype)VALMET (prototype)