Intelligent clinical decision support system for intracranial aneurysm lesion-based detection using biomedical imaging data

Intelligent clinical decision support system for intracranial aneurysm lesion-based detection using biomedical imaging data. Intelligent clinical decision support system for intracranial aneurysm lesion-based detection using biomedical imaging data Article Open access Published: 01 November 2026 Cite this article You have full access to this open access article Download PDF View saved research Intelligent clinical decision support system for intracranial aneurysm lesion-based detection using biomedical imaging data Download PDF Abstract An intracranial aneurysm (IA) is a type of cerebrovascular condition that occurs due to focal bulging or expansion in the wall of a cerebral artery, most frequently affecting the internal carotid artery. An IA is seemingly connected with conditions such as fibrous dysplasia, adult-dominant polycystic kidney disease (ADPKD), and coarctation of aorta.

A ruptured brain aneurysm can result in a severe and life-threatening subarachnoid hemorrhage if not treated early, often leading to long-lasting neurological damage and a higher chance of death. The traditional diagnostic technique is time-consuming, and it necessitates a trained and skilled medical practitioner. Hence, building an automated model to help physicians precisely detect IA can reduce the clinicians’ burden.

Recently, deep learning has gained significant interest in the domain of medical imaging as it automatically learns patterns and accurately detects several types of diseases, such as IAs. The main purpose of this work is to develop a solid system that can automatically detect and identify intracranial aneurysms using medical imaging data to assist clinicians with treatment decisions.

Medical Disclaimer: This article is for informational purposes only and does not constitute medical advice. Always consult with qualified healthcare professionals for medical decisions and treatment options.