Keywords: Machine Learning/Artificial Intelligence, Machine Learning/Artificial Intelligence, Aneurysm detection, nnDetection, Aneurysm LocalizationIntracranial 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
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