Full-resolution network and dual-threshold iteration for retinal vessel and coronary angiograph segmentation

W Liu, H Yang, T Tian, Z Cao, X Pan… - IEEE journal of …, 2022 - ieeexplore.ieee.org
Vessel segmentation is critical for disease diagnosis and surgical planning. Recently, the
vessel segmentation method based on deep learning has achieved outstanding …

Deep learning for 3D vascular segmentation in hierarchical phase contrast tomography: a case study on kidney

E Yagis, S Aslani, Y Jain, Y Zhou, S Rahmani… - Scientific Reports, 2024 - nature.com
Automated blood vessel segmentation is critical for biomedical image analysis, as vessel
morphology changes are associated with numerous pathologies. Still, precise segmentation …

Current state and future perspectives of artificial intelligence for automated coronary angiography imaging analysis in patients with ischemic heart disease

MA Molenaar, JL Selder, J Nicolas, BE Claessen… - Current cardiology …, 2022 - Springer
Abstract Purpose of Review Artificial intelligence (AI) applications in (interventional)
cardiology continue to emerge. This review summarizes the current state and future …

VSSC Net: vessel specific skip chain convolutional network for blood vessel segmentation

PM Samuel, T Veeramalai - Computer methods and programs in …, 2021 - Elsevier
Background and objective Deep learning techniques are instrumental in developing network
models that aid in the early diagnosis of life-threatening diseases. To screen and diagnose …

Progressive perception learning for main coronary segmentation in X-ray angiography

H Zhang, Z Gao, D Zhang, WK Hau… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Main coronary segmentation from the X-ray angiography images is important for the
computer-aided diagnosis and treatment of coronary disease. However, it confronts the …

AngioNet: A convolutional neural network for vessel segmentation in X-ray angiography

K Iyer, CP Najarian, AA Fattah, CJ Arthurs… - Scientific Reports, 2021 - nature.com
Abstract Coronary Artery Disease (CAD) is commonly diagnosed using X-ray angiography,
in which images are taken as radio-opaque dye is flushed through the coronary vessels to …

Prediction of arabica coffee production using artificial neural network and multiple linear regression techniques

Y Kittichotsatsawat, N Tippayawong… - Scientific Reports, 2022 - nature.com
Crop yield and its prediction are crucial in agricultural production planning. This study
investigates and predicts arabica coffee yield in order to match the market demand, using …

The application of deep learning for the segmentation and classification of coronary arteries

Ş Kaba, H Haci, A Isin, A Ilhan, C Conkbayir - Diagnostics, 2023 - mdpi.com
In recent years, the prevalence of coronary artery disease (CAD) has become one of the
leading causes of death around the world. Accurate stenosis detection of coronary arteries is …

Vessel segmentation for X-ray coronary angiography using ensemble methods with deep learning and filter-based features

Z Gao, L Wang, R Soroushmehr, A Wood, J Gryak… - BMC Medical …, 2022 - Springer
Background Automated segmentation of coronary arteries is a crucial step for computer-
aided coronary artery disease (CAD) diagnosis and treatment planning. Correct delineation …

[HTML][HTML] Residual-attention unet++: a nested residual-attention u-net for medical image segmentation

Z Li, H Zhang, Z Li, Z Ren - Applied Sciences, 2022 - mdpi.com
Image segmentation is a basic technology in the field of image processing and computer
vision. Medical image segmentation is an important application field of image segmentation …