The use of fundus images for the early screening of eye diseases is of great clinical
importance. Due to its powerful performance, deep learning is becoming more and more …

Brain tumors are often fatal. Therefore, accurate brain tumor image segmentation is critical
for the diagnosis, treatment, and monitoring of patients with these tumors. Magnetic …

Various deep learning methods have been proposed to segment breast lesions from
ultrasound images. However, similar intensity distributions, variable tumor morphologies …

Colonoscopy is an effective technique for detecting colorectal polyps, which are highly
related to colorectal cancer. In clinical practice, segmenting polyps from colonoscopy …

Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to
face an existential health crisis. Automated detection of lung infections from computed …

Vessel segmentation is critical for disease diagnosis and surgical planning. Recently, the
vessel segmentation method based on deep learning has achieved outstanding …

The precise segmentation of retinal blood vessels is of great significance for early diagnosis
of eye-related diseases such as diabetes and hypertension. In this work, we propose a …

Abstract Camouflaged Object Detection (COD) aims to detect objects with similar patterns
(eg, texture, intensity, colour, etc) to their surroundings, and recently has attracted growing …

In medical image analysis, it is typical to collect multiple annotations, each from a different
clinical expert or rater, in the expectation that possible diagnostic errors could be mitigated …

Optical Coherence Tomography Angiography (OCTA) is a non-invasive imaging technique
that has been increasingly used to image the retinal vasculature at capillary level resolution …