5 citations · 5 across the 7 of their papers we have counts for
7 papers
Learning Prostate Anatomy at Test Time for Cancer Detection in Micro-Ultrasound
Obed Korshie Dzikunu, Mohammad Mahdi Abootorabi, Mohamed Harmanani +7
Domain shift across clinical centers using different imaging hardware or acquisition protocols remains a fundamental barrier to deploying deep learning models for prostate cancer (…
Compass: Prostate Cancer Detection Needs Multi-View Context
Paul F. R. Wilson, Mohamed Harmanani, Zhuoxin Guo +6
Artificial intelligence (AI) analysis of micro-ultrasound (US) has shown promise for prostate cancer (PCa) detection. However, most existing AI methods focus on the analysis of…
Learning Where to Look: A Reinforcement Learning Framework for Robust Micro-Ultrasound Prostate Cancer Detection
Mohammad Mahdi Abootorabi, Sina Namazi, Armin Saadat +7
Micro-ultrasound (US) is a new, emerging, and promising imaging modality for prostate cancer (PCa) detection, but accurate identification of suspicious tissue remains highly dep…
GUIDE-US: Grade-Informed Unpaired Distillation of Encoder Knowledge from Histopathology to Micro-UltraSound
Emma Willis, Tarek Elghareb, Paul F. R. Wilson +6
Purpose: Non-invasive grading of prostate cancer (PCa) from micro-ultrasound (micro-US) could expedite triage and guide biopsies toward the most aggressive regions, yet current mod…
ProstNFound+: A Prospective Study using Medical Foundation Models for Prostate Cancer Detection
Paul F. R. Wilson, Mohamed Harmanani, Minh Nguyen Nhat To +7
Purpose: Medical foundation models (FMs) offer a path to build high-performance diagnostic systems. However, their application to prostate cancer (PCa) detection from micro-ultraso…
TRUSWorthy: Toward Clinically Applicable Deep Learning for Confident Detection of Prostate Cancer in Micro-Ultrasound
Mohamed Harmanani, Paul F. R. Wilson, Minh Nguyen Nhat To +6
While deep learning methods have shown great promise in improving the effectiveness of prostate cancer (PCa) diagnosis by detecting suspicious lesions from trans-rectal ultrasound…
Calibrated Diverse Ensemble Entropy Minimization for Robust Test-Time Adaptation in Prostate Cancer Detection
Mahdi Gilany, Mohamed Harmanani, Paul Wilson +6
High resolution micro-ultrasound has demonstrated promise in real-time prostate cancer detection, with deep learning becoming a prominent tool for learning complex tissue propertie…