5 papers · 1 filter
AS-Mamba: Asymmetric Self-Guided Mamba Decoupled Iterative Network for Metal Artifact Reduction
Bowen Ning, Zekun Zhou, Xinyi Zhong +5
Metal artifact significantly degrades Computed Tomography (CT) image quality, impeding accurate clinical diagnosis. However, existing deep learning approaches, such as CNN and Tran…
Hybrid-View Attention Network for Clinically Significant Prostate Cancer Classification in Transrectal Ultrasound
Zetian Feng, Juan Fu, Xuebin Zou +4
Prostate cancer (PCa) is a leading cause of cancer-related mortality in men, and accurate identification of clinically significant PCa (csPCa) is critical for timely intervention.…
A Narrative Review of Image Processing Techniques Related to Prostate Ultrasound
Haiqiao Wang, Hong Wu, Zhuoyuan Wang +4
Prostate cancer (PCa) poses a significant threat to men's health, with early diagnosis being crucial for improving prognosis and reducing mortality rates. Transrectal ultrasound (T…
Towards Multi-modality Fusion and Prototype-based Feature Refinement for Clinically Significant Prostate Cancer Classification in Transrectal Ultrasound
Hong Wu, Juan Fu, Hongsheng Ye +4
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…
Multi-modality transrectal ultrasound video classification for identification of clinically significant prostate cancer
Hong Wu, Juan Fu, Hongsheng Ye +4
Prostate cancer is the most common noncutaneous cancer in the world. Recently, multi-modality transrectal ultrasound (TRUS) has increasingly become an effective tool for the guidan…