nnDetection for Intracranial Aneurysms Detection and Localization

Intracranial aneurysms are a commonly occurring and lifethreatening condition, affecting approximately 3.2% of the general population. Consequently, the detection of these aneurysms plays a crucial role in their management. Lesion detection involves the simultaneous localization and categorization of abnormalities within medical images. In this particular study, we employed the nnDetection framework, a selfconfiguring framework specifically designed for 3D medical object detection, to effectively detect and localize the 3D coordinates of aneurysms. To capture and extract diverse features associated with aneurysms, we utilized two modalities: TOF-MRA and structural MRI, both obtained from the ADAM dataset. The performance of our proposed deep learning model was assessed through the utilization of free-response receiver operative characteristics for evaluation purposes.