Research progress on deep learning in magnetic resonance imaging–based diagnosis and treatment of prostate cancer: a review on the current status and perspectives

Multiparametric magnetic resonance imaging (mpMRI) has emerged as a first-line screening and diagnostic tool for prostate cancer, aiding in treatment selection noninvasive radiotherapy guidance. However, the manual interpretation of MRI data is challenging time-consuming, which may impact sensitivity specificity. With recent technological advances, artificial intelligence (AI) form computer-aided diagnosis (CAD) based on been applied to cancer treatment. Among AI techniques, deep learning involving convolutional neural networks contributes detection, segmentation, scoring, grading, prognostic evaluation cancer. CAD systems have automatic operation, rapid processing, accuracy, incorporating multiple sequences multiparametric gland into model. Thus, they become research direction great interest, especially smart healthcare. This review highlights current progress technology MRI-based The key elements learning-based image processing are briefly described, making it understandable not only radiologists but also general physicians without specialized training. Deep enables lesion identification, grading scoring prediction postoperative recurrence outcomes. accuracy can be improved by optimizing models algorithms, expanding medical database resources, combining multi-omics comprehensive analysis various morphological data. potential method future.