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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Automatic Segmentation of the Articular Cartilage in Knee MRI Using a Hierarchical Multi-class Classification Scheme
verfasst von : Jenny Folkesson, Erik Dam, Ole Fogh Olsen, Paola Pettersen, Claus Christiansen
Erschienen in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005
Verlag: Springer Berlin Heidelberg
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Osteoarthritis is characterized by the degeneration of the articular cartilage in joints. We have developed a fully automatic method for segmenting the articular cartilage in knee MR scans based on supervised learning. A binary approximate kNN classifier first roughly separates cartilage from background voxels, then a three-class classifier assigns one of three classes to each voxel that is classified as cartilage by the binary classifier. The resulting sensitivity and specificity are 90.0% and 99.8% respectively for the medial cartilage compartments. We show that an accurate automatic cartilage segmentation is achievable using a low-field MR scanner.