5 citations · 5 across the 4 of their papers we have counts for
3 papers · 1 filter
Simulation-Driven Training of Vision Transformers Enabling Metal Segmentation in X-Ray Images
Fuxin Fan, Ludwig Ritschl, Marcel Beister +5
In several image acquisition and processing steps of X-ray radiography, knowledge of the existence of metal implants and their exact position is highly beneficial (e.g. dose regula…
Automated detection and quantification of COVID-19 airspace disease on chest radiographs: A novel approach achieving radiologist-level performance using a CNN trained on digital reconstructed radiographs (DRRs) from CT-based ground-truth
Eduardo Mortani Barbosa, Warren B. Gefter, Rochelle Yang +13
Purpose: To leverage volumetric quantification of airspace disease (AD) derived from a superior modality (CT) serving as ground truth, projected onto digitally reconstructed radiog…
Deep Learning-based Denoising of Mammographic Images using Physics-driven Data Augmentation
Dominik Eckert, Sulaiman Vesal, Ludwig Ritschl +2
Mammography is using low-energy X-rays to screen the human breast and is utilized by radiologists to detect breast cancer. Typically radiologists require a mammogram with impeccabl…