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ct-scan-images

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Developing a well-documented repository for the Lung Nodule Detection task on the Luna16 dataset. This work is inspired by the ideas of the first-placed team at DSB2017, "grt123".

  • Updated Sep 8, 2021
  • Jupyter Notebook

A rule-based algorithm enabled the automatic extraction of disease labels from tens of thousands of radiology reports. These weak labels were used to create deep learning models to classify multiple diseases for three different organ systems in body CT.

  • Updated May 5, 2021
  • Python

The study works on generating CT images from MRI images, where unsupervised learning was used using VAE-CycleGan. Since the number of samples included in the data set used in the study, and therefore in this case we are in a state of epistemic uncertainty, therefore probabilistic models were used in forming the latent space.

  • Updated Sep 23, 2024
  • Jupyter Notebook

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