Hacker News Reader

Wow, this is fascinating. From a radiology perspective, it could be the missing method for segmenting findings inside a convoluted radiograph.

View on HN

Yes, 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.

Would transfer learning help with that?

Yea 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.

Reply on news.ycombinator.com