Accurate segmentation of lesion areas plays an important role in medical imaging-assisted
diagnosis and treatment. Accurate boundary information can help doctors develop precise …

Diffuse gliomas are malignant brain tumors that grow widespread through the brain. The
complex interactions between neoplastic cells and normal tissue, as well as the treatment …

Medical image segmentation aims to locate lesions within a given image to assist doctors in
diagnosis and treatment, playing a crucial role in improving patient outcomes. Recently, the …

Retinal vessel topology provides unique biological information for the diagnosis of fundus
diseases. However, most existing deep learning-based vessel segmentation methods …

Hyperfluorescence (HF) and reduced autofluorescence (RA) are important biomarkers in
fundus autofluorescence images (FAF) for the assessment of health of the retinal pigment …

Many of the tissues/lesions in the medical images may be ambiguous. Therefore, medical
segmentation is typically annotated by a group of clinical experts to mitigate personal bias. A …

Foundation models have exhibited unprecedented capabilities in tackling many domains
and tasks. Models such as CLIP are currently widely used to bridge cross-modal …

Medical ultrasound image segmentation is crucial to the clinical diagnosis of planning for
medical diseases. However, this task is challenging because of the missing/ambiguous …

Biomedical image segmentation plays a pivotal role in medical imaging, facilitating precise
identification and delineation of anatomical structures and abnormalities. This review …

To fully understand the 3D context of a single image, a visual system must be able to
segment both the visible and occluded regions of objects, while discerning their occlusion …