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anindox8 / Deep-Segmentation-Features-for-Weakly-Supervised-3D-Disease-Classification-in-Chest-CT

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Weakly supervised 3D classification of multi-disease chest CT scans using multi-resolution deep segmentation features via dual-stage CNN architecture (DenseVNet, 3D Residual U-Net).

deep-learning convolutional-neural-networks multi-resolution weakly-supervised-learning resnet50 3d-classification tensorflow-estimator ct-imaging segmentation-features densevnet lung-disease feature-aggregation
  • Updated Oct 7, 2020
  • Python

fitushar / WeaklySupervised-3D-Classification-of-Chest-CT-using-Aggregated-MultiResolution-Segmentation-Feature

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This Repo contains the updated implementation of our paper "Weakly supervised 3D classification of chest CT using aggregated multi-resolution deep segmentation features", Proc. SPIE 11314, Medical Imaging 2020: Computer-Aided Diagnosis, 1131408 (16 March 2020)

deep-learning multi-label-classification tfrecords 3d multi-resolution weakly-supervised-learning 3d-cnn segmentation-models tensorflow2 ct-imaging segmentation-features lung-disease feature-aggregation densevnet3d spie-cad weighted-loss weakly-supervised-classification multi-label-loss weight-binary-crossentrophy spie-cad-2020
  • Updated Jun 18, 2020
  • Python

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