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Wow, this is fascinating. From a radiology perspective, it could be the missing method for segmenting findings inside a convoluted radiograph.
by aabajian 9y ago
Wow, this is fascinating. From a radiology perspective, it could be the missing method for segmenting findings inside a convoluted radiograph.
- AndrewKemendo 9y agoYes, and that's possible now with many different CNNs. The limiting factor is the training/validation/test data in your subject. For example you couldn't implement Mask R-CNN with the COCO dataset as implemented here and get inference on your radiology problem set.
- adyus 9y agoWould transfer learning help with that?
- AndrewKemendo 9y agoYea I mean transfer learning would bring over the first n convolutions so it would be faster than from scratch, but you still need the radiology data to get the last few steps.