This clinic trial aims to validate the working performance of radiologists with or without artificial intelligence (AI) diagnostic tool at neurological diseases diagnosis on brain CT/MRI. Routine diagnosis workflow in real clinical scenario including imaging reading, feature interpretation, differential diagnosis, writing initial report and optimizing revised version. And the gold standards of diagnosis are the histopathology references for brain tumors and the discharge diagnosis integrating all the examination results for the other neurological diseases. The performance of AI-assisted tools on diagnosing should be examined in a clinical process with multiple aspects identical to human radiologists' work before being transformed and putted to use. This study hypothesizes that AI models, trained with over 100,000 patient scans, are non-inferior to radiologists in neurological disease diagnosis on brain CT and MRI. For the secondary end-points, we investigate the performance of AI-radiologist collaboration of reasoning-enhanced AI-assisted systems. We hypothesize that, by visualizing the process of imaging interpretation and diagnosis, reasoning-enhanced AI can not only improve working performance of radiologists but also boost their trust in AI tools.