Category: Deep learning
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Medical Deep Imaging spring school 2021
Our third edition of the spring/summer school on deep learning for medical images will be ‘virtual’ and from 19 to 24 of April 2021. Visit the official website here. As the previous edition, there are some lectures, practices, and social events. Most of the content will be available after the school. The first edition web…
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Install Tensorflow2 or PyTorch/MONAI-dev with conda
Create a TensorFlow conda environment A short summary of conda utilization: This procedure is the same for PyTorch, just download monai-dev.yml and adapt the previous lines. This file includes MONAI-dev prerequisits. then finalize the MONAI-dev installation by first activate your env and then installing the MOANI-dev using (more information here):
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A very fast introduction to image processing
Here are some slides to start with images and fundamental processing (pdf) There are also some funny basic practices using python. You may need to set up a working conda environment. For editing your py files, spyder or PyCharm are nice and efficient python IDEs. Activate a conda environment To create an environment with all…
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Introduction to UNet for image segmentation (TF1)
The short introduction to UNet and its architecture (pdf) The proposed code work fine with Tensorflow 1.15 and keras (almostly outdated…). Download this full archive with code, data, and pre-trained model (214 Mo, TP_UNET_FULL.zip). Then, use the notebooks in notebooks_local directory.