Deep learning for segmentation using an open large-scale dataset in 2D echocardiography

S Leclerc, E Smistad, J Pedrosa… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Delineation of the cardiac structures from 2D echocardiographic images is a common
clinical task to establish a diagnosis. Over the past decades, the automation of this task has …

A deep learning approach for assessment of regional wall motion abnormality from echocardiographic images

K Kusunose, T Abe, A Haga, D Fukuda, H Yamada… - Cardiovascular …, 2020 - jacc.org
Objectives This study investigated whether a deep convolutional neural network (DCNN)
could provide improved detection of regional wall motion abnormalities (RWMAs) and …

How to standardize the measurement of left ventricular ejection fraction

K Kusunose, R Zheng, H Yamada, M Sata - Journal of Medical Ultrasonics, 2022 - Springer
Despite recent advances in imaging for myocardial deformation, left ventricular ejection
fraction (LVEF) is still the most important index for systolic function in daily practice. Its role in …

[HTML][HTML] The role of automated 3D echocardiography for left ventricular ejection fraction assessment

E Spitzer, B Ren, F Zijlstra, NM Van Mieghem… - Cardiac failure …, 2017 - ncbi.nlm.nih.gov
Ejection fraction is one of the most powerful determinants of prognosis and is a crucial
parameter for the determination of cardiovascular therapies in conditions such as heart …

Standardized evaluation system for left ventricular segmentation algorithms in 3D echocardiography

O Bernard, JG Bosch, B Heyde… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Real-time 3D Echocardiography (RT3DE) has been proven to be an accurate tool for left
ventricular (LV) volume assessment. However, identification of the LV endocardium remains …

MV-RAN: Multiview recurrent aggregation network for echocardiographic sequences segmentation and full cardiac cycle analysis

M Li, C Wang, H Zhang, G Yang - Computers in biology and medicine, 2020 - Elsevier
Multiview based learning has generally returned dividends in performance because
additional information can be extracted for the representation of the diversity of different …

Deep atlas network for efficient 3D left ventricle segmentation on echocardiography

S Dong, G Luo, C Tam, W Wang, K Wang, S Cao… - Medical image …, 2020 - Elsevier
We proposed a novel efficient method for 3D left ventricle (LV) segmentation on
echocardiography, which is important for cardiac disease diagnosis. The proposed method …

Fast and fully automatic left ventricular segmentation and tracking in echocardiography using shape-based b-spline explicit active surfaces

J Pedrosa, S Queirós, O Bernard… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
Cardiac volume/function assessment remains a critical step in daily cardiology, and 3-D
ultrasound plays an increasingly important role. Fully automatic left ventricular segmentation …

Echocardiographic image multi‐structure segmentation using Cardiac‐SegNet

Y Lei, Y Fu, J Roper, K Higgins, JD Bradley… - Medical …, 2021 - Wiley Online Library
Purpose Cardiac boundary segmentation of echocardiographic images is important for
cardiac function assessment and disease diagnosis. However, it is challenging to segment …

VoxelAtlasGAN: 3D left ventricle segmentation on echocardiography with atlas guided generation and voxel-to-voxel discrimination

S Dong, G Luo, K Wang, S Cao, A Mercado… - … Image Computing and …, 2018 - Springer
Abstract 3D left ventricle (LV) segmentation on echocardiography is very important for
diagnosis and treatment of cardiac disease. It is not only because of that echocardiography …