Automatic Segmentation of articular cartilage is important for the quantitative analysis as well as for 2D or 3D visualization of cartilage. Automatic segmentation of cartilage is quite challenging, particularly for OA patients having Bone Marrow Edema (BME) like lesions. Objective of this study was to develop an automatic segmentation approach which can work well for healthy as well as OA patients with and without BME lesions. In this study we proposed an automatic cartilage segmentation approach based upon modification of radial approach and using T2 map values. Accuracy of proposed method was tested with manual segmentation by computing coefficient of similarity. Proposed automated segmentation method was successfully tested on 12 MRI data set. This method provided an accuracy of 89 ± 1 % DSC in patient without BME and 84 ± 1.7 % in subjects having bone lesions. 2D WearMap of both T2 values and thickness values were generated.
Link to complete publication here:https://scholar.google.com/citations?view_op=view_citation&hl=en&user=dqpMNRUAAAAJ&cstart=20&pagesize=80&citation_for_view=dqpMNRUAAAAJ:IjCSPb-OGe4C
