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

Magnetic resonance imaging (MRI) is a ubiquitous medical imaging technology with
applications in disease diagnostics, intervention, and treatment planning. Accurate MRI …

Generative Adversarial Networks (GAN) have many potential medical imaging applications,
including data augmentation, domain adaptation, and model explanation. Due to the limited …

Mobile artificial intelligence-generated content (AIGC) refers to the adoption of generative
artificial intelligence (GAI) algorithms deployed at mobile edge networks to automate the …

Automated blood vessel segmentation is critical for biomedical image analysis, as vessel
morphology changes are associated with numerous pathologies. Still, precise segmentation …

Deep-learning-based methods have achieved state-of-the-art results in cerebrovascular
segmentation. However, it is costly and time-consuming to acquire labeled data because of …

Purpose Cerebrovascular segmentation from time-of-flight magnetic resonance angiography
(TOF-MRA) is important but challenging for the simulation and measurement of …

Time-of-flight magnetic resonance angiography (TOF-MRA) is a common cerebrovascular
imaging. Accurate and automatic cerebrovascular segmentation in TOF-MRA images is an …