Blood vessel segmentation algorithms—review of methods, datasets and evaluation metrics
Background Blood vessel segmentation is a topic of high interest in medical image analysis
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …
[HTML][HTML] Human treelike tubular structure segmentation: A comprehensive review and future perspectives
Various structures in human physiology follow a treelike morphology, which often expresses
complexity at very fine scales. Examples of such structures are intrathoracic airways, retinal …
complexity at very fine scales. Examples of such structures are intrathoracic airways, retinal …
GC-Net: Global context network for medical image segmentation
J Ni, J Wu, J Tong, Z Chen, J Zhao - Computer methods and programs in …, 2020 - Elsevier
Abstract Background and Objective Medical image segmentation plays an important role in
many clinical applications such as disease diagnosis, surgery planning, and computer …
many clinical applications such as disease diagnosis, surgery planning, and computer …
Attention-assisted adversarial model for cerebrovascular segmentation in 3D TOF-MRA volumes
Cerebrovascular segmentation in time-of-flight magnetic resonance angiography (TOF-
MRA) volumes is essential for a variety of diagnostic and analytical applications. However …
MRA) volumes is essential for a variety of diagnostic and analytical applications. However …
Applicable artificial intelligence for brain disease: A survey
Brain diseases threaten hundreds of thousands of people over the world. Medical imaging
techniques such as MRI and CT are employed for various brain disease studies. As artificial …
techniques such as MRI and CT are employed for various brain disease studies. As artificial …
Global channel attention networks for intracranial vessel segmentation
Intracranial blood vessel segmentation plays an essential role in the diagnosis and surgical
planning of cerebrovascular diseases. Recently, deep convolutional neural networks have …
planning of cerebrovascular diseases. Recently, deep convolutional neural networks have …
All answers are in the images: A review of deep learning for cerebrovascular segmentation
Cerebrovascular imaging is a common examination. Its accurate cerebrovascular
segmentation become an important auxiliary method for the diagnosis and treatment of …
segmentation become an important auxiliary method for the diagnosis and treatment of …
Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation
Deep learning techniques for 3D brain vessel image segmentation have not been as
successful as in the segmentation of other organs and tissues. This can be explained by two …
successful as in the segmentation of other organs and tissues. This can be explained by two …
Generative adversarial network based cerebrovascular segmentation for time-of-flight magnetic resonance angiography image
The accurate segmentation of cerebral vessels from time-of-flight magnetic resonance
angiography (TOF-MRA) data is crucial for the diagnosis and treatment of cerebrovascular …
angiography (TOF-MRA) data is crucial for the diagnosis and treatment of cerebrovascular …
[PDF][PDF] Retinal blood vessel segmentation based on Densely Connected U-Net
Y Cheng, M Ma, L Zhang, C Jin, L Ma, Y Zhou - Math. Biosci. Eng, 2020 - aimspress.com
The segmentation of blood vessels from retinal images is an important and challenging task
in medical analysis and diagnosis. This paper proposes a new architecture of the U-Net …
in medical analysis and diagnosis. This paper proposes a new architecture of the U-Net …