Medical image segmentation is a fundamental and critical step in many image-guided
clinical approaches. Recent success of deep learning-based segmentation methods usually …

Deep learning evolves into a new form of machine learning technology that is classified
under artificial intelligence (AI), which has substantial potential for large-scale healthcare …

Optical coherence tomography angiography (OCTA) is a novel imaging modality that has
been widely utilized in ophthalmology and neuroscience studies to observe retinal vessels …

This paper targets on self-supervised tumor segmentation. We make the following
contributions:(i) we take inspiration from the observation that tumors are often characterised …

Automatic segmentation of curvilinear objects in medical images plays an important role in
the diagnosis and evaluation of human diseases, yet it is a challenging uncertainty in the …

Automated segmentation of pathological fluid regions is crucial for digital diagnosis and
individualized therapy under optical coherence tomography (OCT) images. Nonetheless …

To improve the understanding of potential pathological mechanisms of macular edema
(ME), we try to discover biomarker candidates related to ME caused by diabetic retinopathy …

Objective. Retinal biomarker in optical coherence tomography (OCT) images plays a key
guiding role in the follow-up diagnosis and clinical treatment of eye diseases. Although there …

3D medical image segmentation methods have been successful, but their dependence on
large amounts of voxel-level annotated data is a disadvantage that needs to be addressed …

Layer segmentation of Optical Coherence Tomography (OCT) images is an important step in
diagnosing retinal diseases. However, the presence of some artifacts and noise in OCT …