66 citations · 366 across the 74 of their papers we have counts for
33 papers · 1 filter
Analyzing an Imitation Learning Network for Fundus Image Registration Using a Divide-and-Conquer Approach
Siming Bayer, Xia Zhong, Weilin Fu +2
Comparison of microvascular circulation on fundoscopic images is a non-invasive clinical indication for the diagnosis and monitoring of diseases, such as diabetes and hypertensions…
Deep Learning Algorithms for Coronary Artery Plaque Characterisation from CCTA Scans
Felix Denzinger, Michael Wels, Katharina Breininger +5
Analysing coronary artery plaque segments with respect to their functional significance and therefore their influence to patient management in a non-invasive setup is an important…
Coronary Artery Plaque Characterization from CCTA Scans using Deep Learning and Radiomics
Felix Denzinger, Michael Wels, Nishant Ravikumar +6
Assessing coronary artery plaque segments in coronary CT angiography scans is an important task to improve patient management and clinical outcomes, as it can help to decide whethe…
Epoch-wise label attacks for robustness against label noise
Sebastian Guendel, Andreas Maier
The current accessibility to large medical datasets for training convolutional neural networks is tremendously high. The associated dataset labels are always considered to be the r…
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…
Field of View Extension in Computed Tomography Using Deep Learning Prior
Yixing Huang, Lei Gao, Alexander Preuhs +1
In computed tomography (CT), data truncation is a common problem. Images reconstructed by the standard filtered back-projection algorithm from truncated data suffer from cupping ar…