University of Oulu

J. Thevenot, M. B. López and A. Hadid, "A Survey on Computer Vision for Assistive Medical Diagnosis From Faces," in IEEE Journal of Biomedical and Health Informatics, vol. 22, no. 5, pp. 1497-1511, Sept. 2018. doi: 10.1109/JBHI.2017.2754861

A survey on computer vision for assistive medical diagnosis from faces

Saved in:
Author: Thevenot, Jérôme1; Bordallo López, Miguel2; Hadid, Abdenour2
Organizations: 1Medical Imaging, Physics and Technology Re- search Unit and the Center for Machine Vision and Signal Analysis, Uni- versity of Oulu, Oulu 90014, Finland
2Center for Machine Vision and Signal Analysis, University of Oulu, Oulu 90014, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.6 MB)
Persistent link:
Language: English
Published: Institute of Electrical and Electronics Engineers, 2018
Publish Date: 2018-10-23


Automatic medical diagnosis is an emerging center of interest in computer vision as it provides unobtrusive objective information on a patient’s condition. The face, as a mirror of health status, can reveal symptomatic indications of specific diseases. Thus, the detection of facial abnormalities or atypical features is at upmost importance when it comes to medical diagnostics. This survey aims to give an overview of the recent developments in medical diagnostics from facial images based on computer vision methods. Various approaches have been considered to assess facial symptoms and to eventually provide further help to the practitioners. However, the developed tools are still seldom used in clinical practice, since their reliability is still a concern due to the lack of clinical validation of the methodologies and their inadequate applicability. Nonetheless, efforts are being made to provide robust solutions suitable for healthcare environments, by dealing with practical issues such as real-time assessment or patients positioning. This survey provides an updated collection of the most relevant and innovative solutions in facial images analysis. The findings show that with the help of computer vision methods, over 30 medical conditions can be preliminarily diagnosed from the automatic detection of some of their symptoms. Furthermore, future perspectives, such as the need for interdisciplinary collaboration and collecting publicly available databases, are highlighted.

see all

Series: IEEE journal of biomedical and health informatics
ISSN: 2168-2194
ISSN-E: 2168-2208
ISSN-L: 2168-2194
Volume: 22
Issue: 5
Pages: 1497 - 1511
DOI: 10.1109/JBHI.2017.2754861
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
Copyright information: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.