Service interruption on Monday 11 July from 12:30 to 13:00: all the sites of the CCSD (HAL, EpiSciences, SciencesConf, AureHAL) will be inaccessible (network hardware connection).
Skip to Main content Skip to Navigation
Journal articles

La pathologie cancéreuse pulmonaire à l’heure de l’intelligence artificielle : entre espoir, désespoir et perspectives

Abstract : Histopathology is the fundamental tool of pathology used for more than a century to establish the final diagnosis of lung cancer. In addition, the phenotypic data contained in the histological images reflects the overall effect of molecular alterations on the behavior of cancer cells and provides a practical visual reading of the aggressiveness of the disease. However, the human evaluation of the histological images is sometimes subjective and may lack reproducibility. Therefore, computational analysis of histological imaging using so-called “artificial intelligence” (AI) approaches has recently received considerable attention to improve this diagnostic accuracy. Thus, computational analysis of lung cancer images has recently been evaluated for the optimization of histological or cytological classification, prognostic prediction or genomic profile of patients with lung cancer. This rapidly growing field constantly demonstrates great power in the field of computing medical imaging by producing highly accurate detection, segmentation or recognition tasks. However, there are still several challenges or issues to be addressed in order to successfully succeed the actual transfer into clinical routine. The objective of this review is to emphasize recent applications of AI in pulmonary cancer pathology, but also to clarify the advantages and limitations of this approach, as well as the perspectives to be implemented for a potential transfer into clinical routine.
Document type :
Journal articles
Complete list of metadata

https://hal.inria.fr/hal-02446712
Contributor : Accord Elsevier CCSD Connect in order to contact the contributor
Submitted on : Friday, October 22, 2021 - 5:57:12 PM
Last modification on : Sunday, June 26, 2022 - 3:17:02 AM
Long-term archiving on: : Monday, January 24, 2022 - 5:00:45 PM

File

S0242649819300197.pdf
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution - NonCommercial 4.0 International License

Identifiers

Collections

Citation

Simon Heeke, Hervé Delingette, youta Fanjat, Elodie Long-Mira, Sandra Lassalle, et al.. La pathologie cancéreuse pulmonaire à l’heure de l’intelligence artificielle : entre espoir, désespoir et perspectives. Annales de Pathologie, Elsevier Masson, 2019, 39 (2), pp.130-136. ⟨10.1016/j.annpat.2019.01.003⟩. ⟨hal-02446712⟩

Share

Metrics

Record views

106

Files downloads

43