Lab for Artificial Intelligence in Medical Imaging

PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks for Fully Convolutional Neural Networks

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PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty

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Pytorch Implementation of retinal OCT Layer Segmentation (with trained models)

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Fast Whole Brain Segmentation (Layers, codes and Pre-trained Models)

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Dynamic Affine Feature Map Transform

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Pytorch Implementations of Common modules, blocks and losses for CNNs specifically for segmentation models

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Retinal Layers and Fluid Segmentation in Macular OCT scans (code + Pre-trained Model)

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