Recently, there has been an advancement in the development of innovative computer-aided
techniques for the segmentation and classification of retinal vessels, the application of which …

A popular benchmark for intra-patient lung registration is provided by the DIR-LAB
COPDgene dataset consisting of large-motion in-and expiratory breath-hold CT pairs. This …

To alleviate the demand for a large amount of annotated data by deep learning methods,
this paper explores self-supervised learning (SSL) for brain structure segmentation. Most …

The automated segmentation and analysis of small vessels from in vivo imaging data is an
important task for many clinical applications. While current filtering and learning methods …

Accurately segmenting tubular structures, such as blood vessels or nerves, holds significant
clinical implications across various medical applications. However, existing methods often …

Retinography is a frequently used imaging method that aids in the clinical diagnosis of eye
disorders. Low contrast and being exposed to noise are the primary factors in degraded …

Deep neural networks (DNN) have achieved unprecedented performance in computer-
vision tasks almost ubiquitously in business, technology, and science. While substantial …

Cardiovascular diseases affect a significant part of the population, leading to deterioration in
life quality, health degradation, and even premature death. One of the most effective …

Deep neural networks (DNN) have achieved unprecedented performance in computer-
vision tasks almost ubiquitously in business, technology, and science. While substantial …