Accuracy assessment in convolutional neural network-based deep learning remote sensing studies—Part 1: Literature review
Convolutional neural network (CNN)-based deep learning (DL) is a powerful, recently
developed image classification approach. With origins in the computer vision and image …
developed image classification approach. With origins in the computer vision and image …
Multi-task deep learning for medical image computing and analysis: A review
The renaissance of deep learning has provided promising solutions to various tasks. While
conventional deep learning models are constructed for a single specific task, multi-task deep …
conventional deep learning models are constructed for a single specific task, multi-task deep …
Context-aware network fusing transformer and V-Net for semi-supervised segmentation of 3D left atrium
C Zhao, S Xiang, Y Wang, Z Cai, J Shen, S Zhou… - Expert Systems with …, 2023 - Elsevier
Accurate, robust and automatic segmentation of the left atrium (LA) in magnetic resonance
images (MRI) is of great significance for studying the LA structure and facilitating the …
images (MRI) is of great significance for studying the LA structure and facilitating the …
An efficient anisotropic diffusion model for image denoising with edge preservation
Anisotropic diffusion filtering is a widely used partial differential equation (PDE) based
technique, which works effectively for removal of noise and preserving edges. This …
technique, which works effectively for removal of noise and preserving edges. This …
Dual attention enhancement feature fusion network for segmentation and quantitative analysis of paediatric echocardiography
Paediatric echocardiography is a standard method for screening congenital heart disease
(CHD). The segmentation of paediatric echocardiography is essential for subsequent …
(CHD). The segmentation of paediatric echocardiography is essential for subsequent …
An overview of deep learning methods for left ventricle segmentation
Cardiac health diseases are one of the key causes of death around the globe. The number
of heart patients has considerably increased during the pandemic. Therefore, it is crucial to …
of heart patients has considerably increased during the pandemic. Therefore, it is crucial to …
Stacked dilated convolutions and asymmetric architecture for U-Net-based medical image segmentation
Deep learning has been widely utilized for medical image segmentation. The most
commonly used U-Net and its variants often share two common characteristics but lack solid …
commonly used U-Net and its variants often share two common characteristics but lack solid …
Automatic segmentation of the cardiac MR images based on nested fully convolutional dense network with dilated convolution
H Zhang, W Zhang, W Shen, N Li, Y Chen, S Li… - … signal processing and …, 2021 - Elsevier
Abstract Cardiac Magnetic Resonance Image (MRI) segmentation plays a helpful role in
diagnosing cardiac disease. It is the preliminary step to estimate the functional indices such …
diagnosing cardiac disease. It is the preliminary step to estimate the functional indices such …
Multivariate regression and genetic programming for prediction of backbreak in open-pit blasting
In bench blasting, backbreak is the unwanted result that causes instability to the highwall
and can lead to safety hazards. Hence, it is utmost necessary to minimize the generation of …
and can lead to safety hazards. Hence, it is utmost necessary to minimize the generation of …
Semantic and structural image segmentation for prosthetic vision
Prosthetic vision is being applied to partially recover the retinal stimulation of visually
impaired people. However, the phosphenic images produced by the implants have very …
impaired people. However, the phosphenic images produced by the implants have very …