Segmentation of knee cartilage by using a hierarchical active shape model based on multi-resolution transforms in magnetic resonance images

2013 ◽  
Author(s):  
Madeleine León ◽  
Boris Escalante-Ramirez
Keyword(s):  
Magnetic Resonance ◽  
Magnetic Resonance Images ◽  
Active Shape Model ◽  
Knee Cartilage ◽  
Shape Model ◽  
Model Based ◽  
Active Shape

scholarly journals Creating a 2D Active Shape Model Using itk::ImagePCAShapeModelEstimator

2011 ◽  
Author(s):  
John Durkin ◽  
David Miller ◽  
Kenneth Urish
Keyword(s):  
Active Contour ◽  
Active Shape Model ◽  
Knee Cartilage ◽  
Shape Model ◽  
Active Shape Models ◽  
Contour Segmentation ◽  
Shape Models ◽  
Segmentation Algorithms ◽  
Active Shape ◽  
Weak Boundaries

Although many variations of active contour segmentation algorithms exist, most are based on solely edge criteria and breakdown or leak at weak boundaries. One solution to this problem is constraining the segmented area to only statistically possible shapes with the guidance of a shape model. The purpose of this document is to fill the void in the ITK user guide on building active shape models. We describe how to create a 2d active shape model of articular femoral knee cartilage using ITK’s ImagePCAShapeModelEstimator. Sample code and example images are provided for displaying the initial principle components of variation. Shape models built with our code can be used for segmentation with itk::GeodesicActiveContourShapePriorLevelSetImageFilter.

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