8 citations · 24 across the 15 of their papers we have counts for
15 papers
Vision-Language Models Encode Clinical Guidelines for Concept-Based Medical Reasoning
Mohamed Harmanani, Bining Long, Zhuoxin Guo +6
Concept Bottleneck Models (CBMs) are a prominent framework for interpretable AI that map learned visual features to a set of meaningful concepts for task-specific downstream predic…
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…
TREAT-Net: Tabular-Referenced Echocardiography Analysis for Acute Coronary Syndrome Treatment Prediction
Diane Kim, Minh Nguyen Nhat To, Sherif Abdalla +3
Coronary angiography remains the gold standard for diagnosing Acute Coronary Syndrome (ACS). However, its resource-intensive and invasive nature can expose patients to procedural r…
Domain Knowledge is Power: Leveraging Physiological Priors for Self Supervised Representation Learning in Electrocardiography
Nooshin Maghsoodi, Sarah Nassar, Paul F R Wilson +7
Objective: Electrocardiograms (ECGs) play a crucial role in diagnosing heart conditions; however, the effectiveness of artificial intelligence (AI)-based ECG analysis is often hind…
Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift
Minh Nguyen Nhat To, Paul F RWilson, Viet Nguyen +6
The subpopulationtion shift, characterized by a disparity in subpopulation distributibetween theween the training and target datasets, can significantly degrade the performance of…
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…
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…
Manifold DivideMix: A Semi-Supervised Contrastive Learning Framework for Severe Label Noise
Fahimeh Fooladgar, Minh Nguyen Nhat To, Parvin Mousavi +1
Deep neural networks have proven to be highly effective when large amounts of data with clean labels are available. However, their performance degrades when training data contains…
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…
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…
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…
Methods for Segmentation and Classification of Digital Microscopy Tissue Images
Quoc Dang Vu, Simon Graham, Minh Nguyen Nhat To +11
High-resolution microscopy images of tissue specimens provide detailed information about the morphology of normal and diseased tissue. Image analysis of tissue morphology can help…
Phenomenological Inclusion of Alternative Dispersion Relations to the Teukolsky Equation and its Application to Bounding the Graviton Mass with Gravitational-wave Measurements
Ka-Wai Chung, Tjonnie Guang Feng Li
Existing constraints on the graviton mass from gravitational-wave detections rely on the phase difference developed between different frequencies during the propagation. Effects on…