MultiPlanar UNet: One UNet for all 3-D segmentation Tasks (even if you have less data)- Low Code Approach

Author(s): Sumit Pandey

Originally published on Towards AI.

After beginning my Ph.D., the first real-world medical image segmentation project I encountered involved knee MRI segmentation. I had only 39 labeled MRI images for training and validation and 20 labeled images for a final test set. Moreover, my supervisor added:

“There are almost 200 unlabeled images on which our segmentation model will be tested”

After meeting, I sat at my table and thought, what should I do now U+1F627 ? 39 images are very less, so I did what everyone does: I started with UNet to establish a baseline result. After experimenting with a simple 3D UNet and fine-tuning the hyperparameters… Read the full blog for free on Medium.

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Published via Towards AI