10 citations · 10 across the 3 of their papers we have counts for
3 papers · 1 filter
Clinical Feasibility of Low-Magnification Fluorescence Imaging for Breast Cancer Margin Detection Using Texture Analysis and Deep Learning
Pouya Afshin, Tianling Niu, Tongtong Lu +6
High-resolution images of unprocessed surgical breast tissue can be obtained using microscopy with ultraviolet surface excitation (MUSE). This technique is considered a promising m…
Self-learned representation-guided latent diffusion model for breast cancer classification in deep ultraviolet whole surface images
Pouya Afshin, David Helminiak, Tianling Niu +4
Breast-Conserving Surgery (BCS) requires precise intraoperative margin assessment to preserve healthy tissue. Deep Ultraviolet Fluorescence Scanning Microscopy (DUV-FSM) offers rap…
Deep learning for automated detection of breast cancer in deep ultraviolet fluorescence images with diffusion probabilistic model
Sepehr Salem Ghahfarokhi, Tyrell To, Julie Jorns +3
Data limitation is a significant challenge in applying deep learning to medical images. Recently, the diffusion probabilistic model (DPM) has shown the potential to generate high-q…