16 citations · 24 across the 8 of their papers we have counts for
3 papers · 1 filter
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…
Domain Transfer Through Image-to-Image Translation for Uncertainty-Aware Prostate Cancer Classification
Meng Zhou, Amoon Jamzad, Jason Izard +3
Prostate Cancer (PCa) is a prevalent disease among men, and multi-parametric MRIs offer a non-invasive method for its detection. While MRI-based deep learning solutions have shown…
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…