Neural network: A future in pathology?
Affiliation auteurs | Affiliation ok |
Titre | Neural network: A future in pathology? |
Type de publication | Journal Article |
Year of Publication | 2019 |
Auteurs | Zemouri R, Devalland C, Valmary-Degano S, Zerhouni N |
Journal | ANNALES DE PATHOLOGIE |
Volume | 39 |
Pagination | 119-129 |
Date Published | APR |
Type of Article | Review |
ISSN | 0242-6498 |
Mots-clés | Artificial network, Artificial Neural Networks, Computer-assisted diagnosis, Digital pathology |
Résumé | 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. (C) 2019 Elsevier Masson SAS. All rights reserved. |
DOI | 10.1016/j.annpat.2019.01.004 |