U-Net adaptation for multiple instance learning

Multiple instance learning (MIL) is a weakly supervised learning method where a single label is assigned to a group of instances. Recent advancement in neural networks makes it possible to achieve great results but the training requires many annotated examples which can be difficult to obtain. In case of medical imaging, such a method can theoretically provide voxel-level annotations basing on the image-level annotations. More precisely, taking...