[auraham]

Any recommendations for learning image segmentation for medical images? I would like to learn how to use a pre-trained Keras model like FCN or U-Net. However, most of the resources I've found so far are a bit harder to grasp. Right now, I am reading 'Deep Learning with PyTorch'. The second part of the book covers image segmentation in great detail, but sometimes is too dense. I am familiar with CNNs, convolutions, max pooling, and so on, but not with upscaling and skip connections.

[bertdb]

That book is great if you want to go in-depth! If you're a practitioner who wants to get to a trained model as quickly as possible, you're probably better of just following a tutorial. The official Keras tutorial on segmentation looks pretty good [1]. We also have a blog post with code samples on how to set up an image segmentation workflow with Segments.ai and Facebook's detectron2 framework [2].

[1] https://keras.io/examples/vision/oxford_pets_image_segmentat...

[2] https://segments.ai/blog/speed-up-image-segmentation-with-mo...

[auraham]

Thanks, your tutorial seems great!

[iujjkfjdkkdkf]

If you haven't already, take a look at the detectron2 models and tutorials, especially the colab they have. It is a great way to get started.

https://github.com/facebookresearch/detectron2

[auraham]

Thanks! I was not aware of that model.