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ML challenge organised by french association of radiologists

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JFR-Hackhathon

Annual challenge organised by the french association of radiologists. 2019 edition took place from 14/09 to 13/10, teams were presented with x3 datasets:

  1. TC images of lungs for cancer nodules detection (classification)
  2. TC images of the brain for prediction of multiple sclerosis' level (regrassion: score prediction 1-20)
  3. Calculation of the muscle surface for sarcopenia (segmentation) Present notebooks are a part of lung cancer classification project.

Learning dataset consisted of ~650 3D DICOM images with an typical average resolution of 512x512x350. Images were processed for NN 224x224x3 input to use weights pretrained on the ImageNet. An example of a normalized x3 2D slices stacked to RGB image:

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Link to organiser's web-site: https://jfr.radiologie.fr/presidents-word

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