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1. DIAGNijmegen/prostateMR_3D-CAD-csPCa DIAGNijmegen/prostateMR_3D-CAD-csPCa Public archive

   Hierarchical probabilistic 3D U-Net, with attention mechanisms (—𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘜-𝘕𝘦𝘵, 𝘚𝘌𝘙𝘦𝘴𝘕𝘦𝘵) and a nested decoder structure with deep supervision (—𝘜𝘕𝘦𝘵++). Built in TensorFlow 2.5. Configured for v…

   Python 40 7

2. Deep-Segmentation-Features-for-Weakly-Supervised-3D-Disease-Classification-in-Chest-CT Deep-Segmentation-Features-for-Weakly-Supervised-3D-Disease-Classification-in-Chest-CT Public

   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).

   Python 32 3

3. Ensemble-of-Multi-Scale-CNN-for-Dermatoscopy-Classification Ensemble-of-Multi-Scale-CNN-for-Dermatoscopy-Classification Public

   Fully supervised binary classification of skin lesions from dermatoscopic images using an ensemble of diverse CNN architectures (EfficientNet-B6, Inception-V3, SEResNeXt-101, SENet-154, DenseNet-16…

   Jupyter Notebook 46 16

4. Atlas-Based-3D-Brain-Segmentation-in-T1-MRI Atlas-Based-3D-Brain-Segmentation-in-T1-MRI Public

   Fully supervised, multi-class 3D brain segmentation in T1 MRI, using atlas-based segmentation algorithms (label propagation, tissue models, Expectation-Maximization algorithm).

   Batchfile 7 4

5. Multi-Color-Space-Features-for-Dermatoscopy-Classification Multi-Color-Space-Features-for-Dermatoscopy-Classification Public

   Fully supervised binary classification of skin lesions from dermatoscopic images using multi-color space moments/texture features and Support Vector Machines/Random Forests.

   Jupyter Notebook 8 2

6. Region-Proposal-for-Mass-Detection-in-Mammograms Region-Proposal-for-Mass-Detection-in-Mammograms Public

   Unsupervised region proposal and supervised patch extraction algorithms for extracting candidate 2D ROIs to train SVM/CNN classifiers, for mass detection in mammograms.

   Jupyter Notebook 2 1