Explainable artificial intelligence (XAI) in radiology and nuclear medicine: a literature review

ABSTRACT:

Rational

Deep learning (DL) has demonstrated a remarkable performance in diagnostic imaging for various diseases and modalities and therefore has a high potential to be used as a clinical tool. However, current practice shows low deployment of these algorithms in clinical practice, because DL algorithms lack transparency and trust due to their underlying black-box mechanism. For successful employment, explainable artificial intelligence (XAI) could be introduced to close the gap between the medical professionals and the DL algorithms. In this literature review, XAI methods available for magnetic resonance (MR), computed tomography (CT), and positron emission tomography (PET) imaging are discussed and future suggestions are made.

Methods

PubMed, Embase.com and Clarivate An

SUBMITTER: de Vries B 

PROVIDER: S-EPMC10213317 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature