Contribution of CT-Scan Analysis by Artificial Intelligence to the Clinical Care of TBI Patients

Clément Brossard; Benjamin Lemasson; Arnaud Attyé; Jules-Arnaud de Busschère; Jean-François Payen; Emmanuel L Barbier; Jules Grèze; Pierre Bouzat

doi:10.3389/fneur.2021.666875

Contribution of CT-Scan Analysis by Artificial Intelligence to the Clinical Care of TBI Patients

Front Neurol. 2021 Jun 10:12:666875. doi: 10.3389/fneur.2021.666875. eCollection 2021.

Authors

Clément Brossard¹, Benjamin Lemasson¹, Arnaud Attyé¹, Jules-Arnaud de Busschère¹, Jean-François Payen¹, Emmanuel L Barbier¹, Jules Grèze¹, Pierre Bouzat¹

Affiliation

¹ Université Grenoble Alpes, Inserm, CHU Grenoble Alpes, U1216, Grenoble Institut Neurosciences, Grenoble, France.

Abstract

The gold standard to diagnose intracerebral lesions after traumatic brain injury (TBI) is computed tomography (CT) scan, and due to its accessibility and improved quality of images, the global burden of CT scan for TBI patients is increasing. The recent developments of automated determination of traumatic brain lesions and medical-decision process using artificial intelligence (AI) represent opportunities to help clinicians in screening more patients, identifying the nature and volume of lesions and estimating the patient outcome. This short review will summarize what is ongoing with the use of AI and CT scan for patients with TBI.

Keywords: artificial intelligence; classification; computed tomography; review; segmentation; traumatic brain injury.

Publication types

Review