[Neural network: A future in pathology?].

Journal: Annales de pathologie
Published Date:

Abstract

Artificial Intelligence, in particular deep neural networks are the most used machine learning technics in the biomedical field. Artificial neural networks are inspired by the biological neurons; they are interconnected and follow mathematical models. Two phases are required: a learning and a using phase. The two main applications are classification and regression Computer tools such as GPU computational accelerators or some development tools such as MATLAB libraries are used. Their application field is vast and allows the management of big data in genomics and molecular biology as well as the automated analysis of histological slides. The Whole Slide Image scanner can acquire and store slides in the form of digital images. This scanning associated with deep learning algorithms allows automatic recognition of lesions through the automatic recognition of regions of interest previously validated by the pathologist. These computer aided diagnosis techniques are tested in particular in mammary pathology and dermatopathology. They will allow an efficient and a more comprehensive vision, and will provide diagnosis assistance in pathology by correlating several biomedical data such as clinical, radiological and molecular biology data.

Authors

  • Ryad Zemouri
    CEDRIC laboratory of the Conservatoire national des arts et métiers (CNAM), HESAM université, 292, rue Saint-Martin, 750141 Paris cedex 03, France. Electronic address: ryad.zemouri@cnam.fraa.
  • Christine Devalland
    Service d'anatomie et cytologie pathologiques, hôpital nord Franche-Comté, 100, route de Moval, 90400 Trevenans, France. Electronic address: Christine.devalland@hnfc.fr.
  • Séverine Valmary-Degano
    TSA10217, service d'anatomie et cytologie pathologiques, CHU de Grenoble-Alpes, 38043 Grenoble cedex, France. Electronic address: svalmarydegano@chu-grenoble.fr.
  • Noureddine Zerhouni