A multi-atlas approach for prostate segmentation in MR images
نویسندگان
چکیده
Prostate segmentation is an important and often mandatory step for several tasks, for example volume estimation, radiotherapy planning and computer-aided detection of prostate cancer. In this paper we evaluate a multi-atlas segmentation technique to segment the prostate from transversal T2-weighted MR images on data from the Prostate MR Image Segmentation Challenge (PROMISE12). Atlases are registered using localized mutual information as a metric, after which the Selective and Iterative Method for Performance Level Estimation (SIMPLE)algorithm is used to merge the atlas labels and obtain the final segmentation. Results obtained on the training data show good performance on average with a median Dice coefficient 0.83.
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