Multi-Modal Detection and Localization of Intracranial Aneurysms using 3D nnDetection Deep Learning Model

Intracranial aneurysms are relatively common life-threatening diseases with a prevalence of 3.2% in the general population. Therefore, detection is a vital task in aneurysm management. Lesion detection refers to simultaneously localizing and categorizing the lesions in medical images. In this study, we employed nnDetection framework, a self-configuring framework for 3D medical object detection, to detect and localize the 3D coordination of aneurysms. To capture and extract diverse features of aneurysms, two modalities including TOF-MRA, and structural MRI from ADAM dataset have been used. The performance of the proposed deep learning model was evaluated by free-response receiver operative characteristics