Towards Multi-modality Fusion and Prototype-based Feature Refinement for Clinically Significant Prostate Cancer Classification in Transrectal Ultrasound

arXiv:2406.14069v1 Announce Type: cross
Abstract: Prostate cancer is a highly prevalent cancer and ranks as the second leading cause of cancer-related deaths in men globally. Recently, the utilization of multi-modality transrectal ultrasound (TRUS) has gained significant traction as a valuable technique for guiding prostate biopsies. In this study, we propose a novel learning framework for clinically significant prostate cancer (csPCa) classification using multi-modality TRUS. The proposed framework employs two separate 3D ResNet-50 to extract distinctive features from B-mode and shear …

arxiv cancer classification cs.cv eess.iv feature fusion prostate cancer prototype type