I am wondering if there is a simple 3D Mask-RCNN code? Also, is there trained models that I can simply just import like ResNet. Please note that I need 3D not 2D.
Any other state-of-the-art 3D semantic segmentation/Instance segmentation models?
I am not aware of any pre-packaged (or pre-trained) 3D Mask-RCNN
implementations.
A search will lead you to a number of pytorch 3D U-Net implementations.
(I don’t know which, if any, of them are any good.)
Be aware that U-Net performs semantic (not instance) segmentation.
(People do get good instance segmentation from U-Net in some use
cases by post-processing (e.g., running connected components) the
results of U-Net’s semantic segmentation.)
Note, for 3D images of any size, any such 3D model will quickly become
resource hungry, both in terms of memory and computation time.
Thank you very much. I have tried U-nets for Semantic segmentation and now I am looking for something different to U-net to see if it would make any difference. And you are absolutely correct about resource problem, it is the most difficult part dealing with 3D-Unets for me.