Optical coherence tomography (OCT) is a prevalent non-invasive imaging method which
provides high resolution volumetric visualization of retina. However, its inherent defect, the …

Optical coherence tomography angiography (OCTA) is an imaging modality that can be
used for analyzing retinal vasculature. Quantitative assessment of en face OCTA images …

Blessed by vast amounts of data, learning-based methods have achieved remarkable
performance in countless tasks in computer vision and medical image analysis. Although …

Recently, deep learning methods have achieved state-of-the-art performance in many
medical image segmentation tasks. Many of these are based on convolutional neural …

The zebrafish is an established vertebrae model in the field of biomedical research. With its
small size, rapid maturation time and semi-transparency at early development stages, it has …

Optical coherence tomography (OCT) has become the gold standard for ophthalmic
diagnostic imaging. However, clinical OCT image-quality is highly variable and limited …

Segmentation of blood vessels in murine cerebral 3D OCTA images is foundational for in
vivo quantitative analysis of the effects of neurovascular disorders, such as stroke or …

Optical coherence tomography angiography (OCTA) offers critical insights into the retinal
vascular system, yet its full potential is hindered by challenges in precise image …

Deep models suffer from limited generalization capability to unseen domains, which has
severely hindered their clinical applicability. Specifically for the retinal vessel segmentation …

Abstract Domain generalization has great impact on medical image analysis as data
distribution inconsistencies are prevalent in most of the medical data modalities due to the …