Deep learning in cardiology
P Bizopoulos, D Koutsouris - IEEE reviews in biomedical …, 2018 - ieeexplore.ieee.org
The medical field is creating large amount of data that physicians are unable to decipher
and use efficiently. Moreover, rule-based expert systems are inefficient in solving …
and use efficiently. Moreover, rule-based expert systems are inefficient in solving …
[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 …
Hard attention net for automatic retinal vessel segmentation
D Wang, A Haytham, J Pottenburgh… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Automated retinal vessel segmentation is among the most significant application and
research topics in ophthalmologic image analysis. Deep learning based retinal vessel …
research topics in ophthalmologic image analysis. Deep learning based retinal vessel …
A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification
The eye affords a unique opportunity to inspect a rich part of the human microvasculature
non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are …
non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are …
Review of machine learning applications using retinal fundus images
Y Jeong, YJ Hong, JH Han - Diagnostics, 2022 - mdpi.com
Automating screening and diagnosis in the medical field saves time and reduces the
chances of misdiagnosis while saving on labor and cost for physicians. With the feasibility …
chances of misdiagnosis while saving on labor and cost for physicians. With the feasibility …
ELEMENT: Multi-modal retinal vessel segmentation based on a coupled region growing and machine learning approach
Vascular structures in the retina contain important information for the detection and analysis
of ocular diseases, including age-related macular degeneration, diabetic retinopathy and …
of ocular diseases, including age-related macular degeneration, diabetic retinopathy and …
CSGNet: Cascade semantic guided net for retinal vessel segmentation
S Guo - Biomedical Signal Processing and Control, 2022 - Elsevier
Retinal vessels are essential biomarkers for the early diagnosis of ophthalmic diseases.
Accurate segmentation of retinal vessels is necessary for further quantitative analysis of …
Accurate segmentation of retinal vessels is necessary for further quantitative analysis of …
Cross-attention multi-branch network for fundus diseases classification using SLO images
Fundus diseases classification is vital for the health of human beings. However, most of
existing methods detect diseases by means of single angle fundus images, which lead to the …
existing methods detect diseases by means of single angle fundus images, which lead to the …
A retinal vessel segmentation method based improved U-Net model
K Sun, Y Chen, Y Chao, J Geng, Y Chen - Biomedical Signal Processing …, 2023 - Elsevier
There are two problems in retinal blood vessel segmentation, which are the insufficient
segmentation of small vessels due to the complex curvature morphology of blood vessels …
segmentation of small vessels due to the complex curvature morphology of blood vessels …
Dense residual network for retinal vessel segmentation
Retinal vessel segmentation plays an imaportant role in the field of retinal image analysis
because changes in retinal vascular structure can aid in the diagnosis of diseases such as …
because changes in retinal vascular structure can aid in the diagnosis of diseases such as …