Current Landscape of Generative Adversarial Networks for Facial Deidentification in Dermatology: Systematic Review and Evaluation.

ABSTRACT:

Background

Deidentifying facial images is critical for protecting patient anonymity in the era of increasing tools for automatic image analysis in dermatology.

Objective

The aim of this paper was to review the current literature in the field of automatic facial deidentification algorithms.

Methods

We conducted a systematic search using a combination of headings and keywords to encompass the concepts of facial deidentification and privacy preservation. The MEDLINE (via PubMed), Embase (via Elsevier), and Web of Science (via Clarivate) databases were queried from inception to May 1, 2021. Studies of incorrect design and outcomes were excluded during the screening and review process.

Results

A total of 18 studies reporting on various methodologies of facial deiden

SUBMITTER: Park C 

PROVIDER: S-EPMC10334885 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature