The AiCOLO project associates computer scientists, specialized in data and image analysis, with pathologists and biostatisticians, specialized in digital pathology and colon cancer. This project focuses on two methodological aspects of WSI imaging, at the convergence of image analysis and data-mining, with specific objectives:
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Features extraction and coarse image classification for determining basic regions of interest and biological objects (e.g. tumor, stromal structures, vessels, muscle, immune infiltrate, normal tissue) using deep learning frameworks that have proven their efficiency in such problems with the aim to use these data to define patients prognosis. The task will be to develop a new tool to assist pathologists by giving an automatic estimation of the prognosis using digitized WSI.
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Use of deep neural network to predict colon cancer genetic features and describe the tissue features built by the neural network to make this prediction.
More details here…
News:
- 2022-09-24: Publication accepted in Artificial Intelligence in Medecine (more info here…)
- 2022-02-02: Publication accepted at 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - VISAPP (more info here…)
- 2021-08-04: Publication accepted in Computers in Biology and Medecine (more info here…)
- 2020-09 / 2021-02: Internship of Ilias Rmouque on auto-encoders for unsupervised clustering of colon cancer WSI
- 2020-09-01: Welcome to Amina Ben Hamida who joins the project as postdoc
- 2019-11-27: Kick-off meeting of the project in Dijon!
- 2019-10-24: Open position for a three years postdoctoral research in deep learning for histopathological image analysis (more info here…)