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  1. 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 27 2

  2. 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 24 2

  3. 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 22 13

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

    Batchfile 5 3

  5. 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 5 2

  6. 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

224 contributions in the last year

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Contribution activity

March 2022

Opened 1 issue in 1 repository
comic/grand-challenge.org 1 open

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