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20192025
most citedImage quality assessment for machine learning tasks using meta-reinforcement learning

51 citations · 134 across the 15 of their papers we have counts for

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eess.IV20251 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.IV20253 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…

eess.IV2024

BreastRegNet: A Deep Learning Framework for Registration of Breast Faxitron and Histopathology Images

Negar Golestani, Aihui Wang, Gregory R Bean +1

A standard treatment protocol for breast cancer entails administering neoadjuvant therapy followed by surgical removal of the tumor and surrounding tissue. Pathologists typically r…

eess.IV2023

ProsDectNet: Bridging the Gap in Prostate Cancer Detection via Transrectal B-mode Ultrasound Imaging

Sulaiman Vesal, Indrani Bhattacharya, Hassan Jahanandish +8

Interpreting traditional B-mode ultrasound images can be challenging due to image artifacts (e.g., shadowing, speckle), leading to low sensitivity and limited diagnostic accuracy.…