Imaging modalities to diagnose carotid artery stenosis: progress and prospect

A Saxena, EYK Ng, ST Lim - Biomedical engineering online, 2019 - Springer
In the past few decades, imaging has been developed to a high level of sophistication.
Improvements from one-dimension (1D) to 2D images, and from 2D images to 3D models …

Breast cancer detection using extreme learning machine based on feature fusion with CNN deep features

Z Wang, M Li, H Wang, H Jiang, Y Yao, H Zhang… - IEEE …, 2019 - ieeexplore.ieee.org
A computer-aided diagnosis (CAD) system based on mammograms enables early breast
cancer detection, diagnosis, and treatment. However, the accuracy of the existing CAD …

Carotid wall longitudinal motion in ultrasound imaging: an expert consensus review

FY Rizi, J Au, H Yli-Ollila, S Golemati… - Ultrasound in Medicine …, 2020 - Elsevier
Motion extracted from the carotid artery wall provides unique information for vascular health
evaluation. Carotid artery longitudinal wall motion corresponds to the multiphasic arterial …

Clinical interpretable deep learning model for glaucoma diagnosis

WM Liao, BJ Zou, RC Zhao, YQ Chen… - IEEE journal of …, 2019 - ieeexplore.ieee.org
Despite the potential to revolutionise disease diagnosis by performing data-driven
classification, clinical interpretability of ConvNet remains challenging. In this paper, a novel …

Learning physical properties in complex visual scenes: An intelligent machine for perceiving blood flow dynamics from static CT angiography imaging

Z Gao, X Wang, S Sun, D Wu, J Bai, Y Yin, X Liu… - Neural Networks, 2020 - Elsevier
Humans perceive physical properties such as motion and elastic force by observing objects
in visual scenes. Recent research has proven that computers are capable of inferring …

Learning tree-structured representation for 3D coronary artery segmentation

B Kong, X Wang, J Bai, Y Lu, F Gao, K Cao… - … Medical Imaging and …, 2020 - Elsevier
Extensive research has been devoted to the segmentation of the coronary artery. However,
owing to its complex anatomical structure, it is extremely challenging to automatically …

A deep learning-based approach for automatic segmentation and quantification of the left ventricle from cardiac cine MR images

H Abdeltawab, F Khalifa, F Taher, NS Alghamdi… - … medical imaging and …, 2020 - Elsevier
Cardiac MRI has been widely used for noninvasive assessment of cardiac anatomy and
function as well as heart diagnosis. The estimation of physiological heart parameters for …

Privileged modality distillation for vessel border detection in intracoronary imaging

Z Gao, J Chung, M Abdelrazek, S Leung… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Intracoronary imaging is a crucial imaging technology in coronary disease diagnosis as it
visualizes the internal tissue morphologies of coronary arteries. Vessel border detection in …

Multi-level semantic adaptation for few-shot segmentation on cardiac image sequences

S Guo, L Xu, C Feng, H **ong, Z Gao, H Zhang - Medical Image Analysis, 2021 - Elsevier
Obtaining manual labels is time-consuming and labor-intensive on cardiac image
sequences. Few-shot segmentation can utilize limited labels to learn new tasks. However, it …

Left ventricle automatic segmentation in cardiac MRI using a combined CNN and U-net approach

B Wu, Y Fang, X Lai - Computerized Medical Imaging and Graphics, 2020 - Elsevier
Cardiovascular diseases can be effectively prevented from worsening through early
diagnosis. To this end, various methods have been proposed to detect the disease source …