Image-segmentation-jupyter-notebook 99%

: A highly interactive notebook using the Oxford-IIIT Pet Dataset. It demonstrates how to use the U-Net architecture to classify every pixel into categories like "pet," "border," or "surrounding".

: If you need to label your own data, Towards Data Science describes building a custom labeling tool directly within a single Jupyter notebook using transfer learning.

: CellPose with SimpleITK is an excellent resource for researchers needing to segment cells or nuclei in microscopy images.

: For 3D MRI or CT scan segmentation, NVIDIA's guide on Medical 3D Image Segmentation focuses on brain tumor prediction.

: This comprehensive guide covers building and training a segmentation model from scratch. It focuses on the architectural details of U-Net and includes a walkthrough for creating custom PyTorch datasets.