BCDU-Net | BCDU-Net : Medical Image Segmentation | Machine Learning library

BCDU-Net is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow, Keras applications. BCDU-Net has no bugs, it has no vulnerabilities and it has low support. However BCDU-Net build file is not available. You can download it from GitHub.

Deep auto-encoder-decoder network for medical image segmentation with state of the art results on skin lesion segmentation, lung segmentation, and retinal blood vessel segmentation. This method applies bidirectional convolutional LSTM layers in U-net structure to non-linearly encode both semantic and high-resolution information with non-linearly technique. Furthermore, it applies densely connected convolution layers to include collective knowledge in representation and boost convergence rate with batch normalization layers. If this code helps with your research please consider citing the following papers:. R. Azad, M. Asadi, Mahmood Fathy and Sergio Escalera "Bi-Directional ConvLSTM U-Net with Densely Connected Convolutions ", ICCV, 2019, download link. M. Asadi, R. Azad, Mahmood Fathy and Sergio Escalera "Multi-level Context Gating of Embedded Collective Knowledge for Medical Image Segmentation", The first two authors contributed equally. arXiv:2003.05056, 2020, download link.