With the improvement of hardware computing power and the development of deep learning
algorithms, a revolution of" artificial intelligence (AI)+ medical image" is taking place …

Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …

Colonoscopy is an effective method for detecting colorectal polyps and preventing colorectal
cancer. Therefore, in clinical practice, it is very important to accurately segment the location …

Automated retinal blood vessel segmentation in fundus images provides important evidence
to ophthalmologists in coping with prevalent ocular diseases in an efficient and non-invasive …

Colorectal cancer is a prevalent disease in modern times, with most cases being caused by
polyps. Therefore, the segmentation of polyps has garnered significant attention in the field …

Convolutional neural networks (CNN), especially numerous U-shaped models, have
achieved great progress in retinal vessel segmentation. However, a great quantity of global …

Medical imaging is a key component in clinical diagnosis, treatment planning and clinical
trial design, accounting for almost 90% of all healthcare data. CNNs achieved performance …

Precise medical image segmentation is a crucial step for proper isolation of target regions,
such as an organ or lesion for accurate medical diagnosis, prognosis and certain medical …

This article provides a comprehensive review of deep learning-based blood vessel
segmentation of the brain. Cerebrovascular disease develops when blood arteries in the …

Multi-modality magnetic resonance imaging (MRI) can reveal distinct patterns of tissue in the
human body and is crucial to clinical diagnosis. But it still remains a challenge to obtain …