Multi-scale deep networks and regression forests for direct bi-ventricular volume estimation
Direct estimation of cardiac ventricular volumes has become increasingly popular and
important in cardiac function analysis due to its effectiveness and efficiency by avoiding an …
important in cardiac function analysis due to its effectiveness and efficiency by avoiding an …
Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation
Fine renal artery segmentation on abdominal CT angiography (CTA) image is one of the
most important tasks for kidney disease diagnosis and pre-operative planning. It will help …
most important tasks for kidney disease diagnosis and pre-operative planning. It will help …
Head pose estimation based on multivariate label distribution
X Geng, X Qian, Z Huo, Y Zhang - IEEE Transactions on Pattern …, 2020 - ieeexplore.ieee.org
Accurate ground-truth pose is essential to the training of most existing head pose estimation
methods. However, in many cases, the “ground truth” pose is obtained in rather subjective …
methods. However, in many cases, the “ground truth” pose is obtained in rather subjective …
MB-FSGAN: Joint segmentation and quantification of kidney tumor on CT by the multi-branch feature sharing generative adversarial network
Y Ruan, D Li, H Marshall, T Miao, T Cossetto… - Medical image …, 2020 - Elsevier
The segmentation of the kidney tumor and the quantification of its tumor indices (ie, the
center point coordinates, diameter, circumference, and cross-sectional area of the tumor) are …
center point coordinates, diameter, circumference, and cross-sectional area of the tumor) are …
Deep atlas network for efficient 3D left ventricle segmentation on echocardiography
We proposed a novel efficient method for 3D left ventricle (LV) segmentation on
echocardiography, which is important for cardiac disease diagnosis. The proposed method …
echocardiography, which is important for cardiac disease diagnosis. The proposed method …
Segmentation and quantification of infarction without contrast agents via spatiotemporal generative adversarial learning
Accurate and simultaneous segmentation and full quantification (all indices are required in a
clinical assessment) of the myocardial infarction (MI) area are crucial for early diagnosis and …
clinical assessment) of the myocardial infarction (MI) area are crucial for early diagnosis and …
A video analytic in-class student concentration monitoring system
MC Su, CT Cheng, MC Chang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Automatic learning feedback monitoring and analysis are becoming essential in modern
education. We present a video analytic system capable of monitoring in-class student's …
education. We present a video analytic system capable of monitoring in-class student's …
Predicting CT image from MRI data through feature matching with learned nonlinear local descriptors
Attenuation correction for positron-emission tomography (PET)/magnetic resonance (MR)
hybrid imaging systems and dose planning for MR-based radiation therapy remain …
hybrid imaging systems and dose planning for MR-based radiation therapy remain …
PV-LVNet: Direct left ventricle multitype indices estimation from 2D echocardiograms of paired apical views with deep neural networks
Accurate direct estimation of the left ventricle (LV) multitype indices from two-dimensional
(2D) echocardiograms of paired apical views, ie, paired apical four-chamber (A4C) and two …
(2D) echocardiograms of paired apical views, ie, paired apical four-chamber (A4C) and two …
Direct automated quantitative measurement of spine by cascade amplifier regression network with manifold regularization
S Pang, Z Su, S Leung, IB Nachum, B Chen… - Medical image …, 2019 - Elsevier
Automated quantitative measurement of the spine (ie, multiple indices estimation of heights,
widths, areas, and so on for the vertebral body and disc) plays a significant role in clinical …
widths, areas, and so on for the vertebral body and disc) plays a significant role in clinical …