activity
20222025
most citedTRUSWorthy: Toward Clinically Applicable Deep Learning for Confident Detection of Prostate Cancer in Micro-Ultrasound

5 citations · 14 across the 7 of their papers we have counts for

collaborators

7 papers

eess.IV2025★ 5 cited

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…

eess.IV2025★ 4 cited

Cinepro: Robust Training of Foundation Models for Cancer Detection in Prostate Ultrasound Cineloops

Mohamed Harmanani, Amoon Jamzad, Minh Nguyen Nhat To +11

Prostate cancer (PCa) detection using deep learning (DL) models has shown potential for enhancing real-time guidance during biopsies. However, prostate ultrasound images lack pixel…

cs.CV2024

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…

eess.IV2024★ 2 cited

Benchmarking Image Transformers for Prostate Cancer Detection from Ultrasound Data

Mohamed Harmanani, Paul F. R. Wilson, Fahimeh Fooladgar +6

PURPOSE: Deep learning methods for classifying prostate cancer (PCa) in ultrasound images typically employ convolutional networks (CNNs) to detect cancer in small regions of intere…

eess.IV2023★ 1 cited

TRUSformer: Improving Prostate Cancer Detection from Micro-Ultrasound Using Attention and Self-Supervision

Mahdi Gilany, Paul Wilson, Andrea Perera-Ortega +6

A large body of previous machine learning methods for ultrasound-based prostate cancer detection classify small regions of interest (ROIs) of ultrasound signals that lie within a l…

eess.IV2022★ 2 cited

Self-Supervised Learning with Limited Labeled Data for Prostate Cancer Detection in High Frequency Ultrasound

Paul F. R. Wilson, Mahdi Gilany, Amoon Jamzad +5

Deep learning-based analysis of high-frequency, high-resolution micro-ultrasound data shows great promise for prostate cancer detection. Previous approaches to analysis of ultrasou…

eess.IV2022

Towards Confident Detection of Prostate Cancer using High Resolution Micro-ultrasound

Mahdi Gilany, Paul Wilson, Amoon Jamzad +5

MOTIVATION: Detection of prostate cancer during transrectal ultrasound-guided biopsy is challenging. The highly heterogeneous appearance of cancer, presence of ultrasound artefacts…