Intracranial aneurysms, abnormal dilations of blood vessels in the brain, pose significant health risks, especially when ruptured, leading to conditions such as subarachnoid hemorrhage and stroke. The primary objective of this study is to evaluate the diagnostic accuracy of different computed tomography angiography (CTA) protocols for detecting intracranial aneurysms and to identify methods for optimizing scanning parameters to reduce radiation exposure while ensuring high image quality. Results from the analysis of various CTA protocols revealed that lowering tube voltages (80-120 kV) and milliampere seconds (mAs) effectively reduced radiation exposure without compromising the quality of images. Additionally, the use of advanced reconstruction algorithms, including deep learning techniques, significantly improved the visualization of small vascular structures, thereby enhancing diagnostic accuracy. These findings provide valuable insights for enhancing clinical practices in the fields of neurology and radiology.