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2018-03-27 - Colloque/Présentation - poster - Anglais - 1 page(s)

El Adoui Mohammed , Benjelloun Mohammed , "The Prediction Of Breast Cancer Response To Chemotherapy By Deep Learning" in Mardi des chercheurs MDC'18, Wallers Arenberg, France, 2018

  • Codes CREF : Techniques d'imagerie et traitement d'images (DI2770)
  • Unités de recherche UMONS : Informatique (F114)
  • Instituts UMONS : Institut de Recherche en Technologies de l’Information et Sciences de l’Informatique (InforTech)

Abstract(s) :

(Anglais) In this work, we used a retrospective study of 40 patients with breast cancer provided by our collaborating center of radiology Jules Bordet in Brussels. Our dataset includes the anatomical pathology as a standard reference of breast tumor response to chemotherapy. We propose a multi input neural network receiving the contrast MRI slices acquired before and after chemotherapy, and provide as output the response probability prediction. We plan to Compare the efficiently of new CNN architecture such as DensNet, NasNet, ResNet.