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Prostate segmentation from Magnetic Resonance (MR) images plays an important role in image guided intervention. However, the lack of clear boundary specifically at the apex and base, and huge variation of shape and texture between the images from different patients make the task very challenging. To overcome these problems, in this paper, we propose a deeply supervised convolutional neural network...
Batch-mode active learning (AL) approaches are dedicated to the training sample set selection for classification, regression, and retrieval problems, where a batch of unlabeled samples is queried at each iteration by considering both the uncertainty and diversity criteria. However, for remote sensing applications, the conventional methods do not consider the spatial coherence between the training...
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