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20242026
most citedMultimodal MRI-Ultrasound AI for Prostate Cancer Detection Outperforms Radiologist MRI Interpretation: A Multi-Center Study

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

The MAMA-MIA Challenge: Advancing Generalizability and Fairness in Breast MRI Tumor Segmentation and Treatment Response Prediction

Lidia Garrucho, Smriti Joshi, Kaisar Kushibar +43

Breast cancer is the most frequently diagnosed malignancy among women worldwide and a leading cause of cancer-related mortality. Dynamic contrast-enhanced magnetic resonance imagin…

eess.IV2025★ 1 cited

Prostate-Specific Foundation Models for Enhanced Detection of Clinically Significant Cancer

Jeong Hoon Lee, Cynthia Xinran Li, Hassan Jahanandish +14

Accurate prostate cancer diagnosis remains challenging. Even when using MRI, radiologists exhibit low specificity and significant inter-observer variability, leading to potential d…

eess.IV2025

Registration-Enhanced Segmentation Method for Prostate Cancer in Ultrasound Images

Shengtian Sang, Hassan Jahanandish, Cynthia Xinran Li +8

Prostate cancer is a major cause of cancer-related deaths in men, where early detection greatly improves survival rates. Although MRI-TRUS fusion biopsy offers superior accuracy by…

eess.IV2025★ 3 cited

Multimodal MRI-Ultrasound AI for Prostate Cancer Detection Outperforms Radiologist MRI Interpretation: A Multi-Center Study

Hassan Jahanandish, Shengtian Sang, Cynthia Xinran Li +6

Pre-biopsy magnetic resonance imaging (MRI) is increasingly used to target suspicious prostate lesions. This has led to artificial intelligence (AI) applications improving MRI-base…

eess.IV2024

Mask Enhanced Deeply Supervised Prostate Cancer Detection on B-mode Micro-Ultrasound

Lichun Zhang, Steve Ran Zhou, Moon Hyung Choi +14

Prostate cancer is a leading cause of cancer-related deaths among men. The recent development of high frequency, micro-ultrasound imaging offers improved resolution compared to con…