Automatic detection of cerebral microbleeds using susceptibility weighted imaging and artificial intelligence.

ABSTRACT:

Background

Efficiently and accurately detecting cerebral microbleeds (CMBs) is crucial for diagnosing dementia, stroke, and traumatic brain injury. Manual CMB detection, however, is time-consuming and error-prone. This study evaluates a novel artificial intelligence (AI) software designed for the automated detection of CMBs using susceptibility weighted imaging (SWI).

Methods

The SWI data from 265 patients, 206 of whom had a history of stroke and others of whom presented a variety of other medical histories, including hypertension, diabetes, hyperlipidemia, cerebral hemorrhage, intracerebral vascular malformations, tumors, and inflammation, collected between January 2015 and December 2018, were analyzed. Two independent radiologists initially reviewed the images to identify

SUBMITTER: Luo Y 

PROVIDER: S-EPMC10963806 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature