In recent years, there has been an unprecedented growth in computer vision and deep
learning implementation owing to the exponential rise of computation infrastructure. The …

Diabetic retinopathy (DR) is a diabetes complication that can cause vision loss among
patients due to damage to blood vessels in the retina. Early retinal screening can avoid the …

Hard exudate plays an important role in grading diabetic retinopathy (DR) as a critical
indicator. Therefore, the accurate segmentation of hard exudates is of clinical importance …

Existing CNN-based segmentation approaches have achieved remarkable progresses on
segmenting objects in regular sizes. However, when migrating them to segment tiny retinal …

Liver vessels generated from computed tomography are usually pretty small, which poses
major challenges for satisfactory vessel segmentation, including 1) the scarcity of high …

Deep learning has found widespread application in diabetic retinopathy (DR) screening,
primarily for lesion detection. However, this approach encounters challenges such as …

The primary prerequisite for multi-lesion segmentation is the simultaneous detection of
multiple lesions. Numerous techniques based on the frameworks of simultaneous multi …

Surgical instrument segmentation plays a crucial role in robot-assisted surgery by furnishing
essential information about instrument location and orientation. This information not only …

Nuclei segmentation is an essential step in DNA ploidy analysis by image-based cytometry
(DNA-ICM) which is widely used in cytopathology and allows an objective measurement of …

Early human intervention is crucial for diagnosing Alzheimer's Disease (AD), since AD is
irreversible and leads to progressive impairment of memory. In recent years, Convolutional …