Survey on machine learning applied to medical image analysis

Aurelien Olivier, Clement Hoffmann, Ali Mansour, Luc Bressollette, Benoit Clement

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a selective survey on recent advances in machine learning applied to medical imaging. It aims to highlight both innovations that increase the performance of the models and methods that ensure certainty, interpretability and robustness of the trained models. The paper focuses particularly on new concepts such as attention modules that allow to gather specific features considering global context. Its second main focus is given to domain adaptation methods to enhance model robustness to distribution shifts. Finally, we discuss uncertainty estimation and interpretability methods to evaluate confidence in a trained model.
Original languageEnglish
Title of host publicationProceedings - 2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2021
EditorsQingli Li, Lipo Wang, Yan Wang, Wenwu Li
Place of PublicationOnline
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781665400046, 9781665400039, 9781665400053
DOIs
Publication statusPublished - 2021
EventInternational Congress on Image and Signal Processing, BioMedical Engineering and Informatics - Shanghai, China
Duration: 23 Oct 2021 → …
Conference number: 14

Publication series

NameProceedings - 2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2021

Conference

ConferenceInternational Congress on Image and Signal Processing, BioMedical Engineering and Informatics
Abbreviated titleCISP-BMEI
Country/TerritoryChina
CityShanghai
Period23/10/21 → …

Keywords

  • Deep learning
  • Machine learning
  • Medical image analysis
  • attention modules
  • domain adaptation
  • uncertainty estimation
  • venous Thrombo-Embolism

Fingerprint

Dive into the research topics of 'Survey on machine learning applied to medical image analysis'. Together they form a unique fingerprint.

Cite this