Left ventricle quantification challenge: A comprehensive comparison and evaluation of segmentation and regression for mid-ventricular short-axis cardiac MR data

W Xue, J Li, Z Hu, E Kerfoot, J Clough… - IEEE journal of …, 2021 - ieeexplore.ieee.org
Automatic quantification of the left ventricle (LV) from cardiac magnetic resonance (CMR)
images plays an important role in making the diagnosis procedure efficient, reliable, and …

Left ventricle quantification using direct regression with segmentation regularization and ensembles of pretrained 2D and 3D CNNs

N Gessert, A Schlaefer - International Workshop on Statistical Atlases and …, 2019 - Springer
Cardiac left ventricle (LV) quantification provides a tool for diagnosing cardiac diseases.
Automatic calculation of all relevant LV indices from cardiac MR images is an intricate task …

Left ventricle quantification with sample-level confidence estimation via Bayesian neural network

W Xue, T Guo, D Ni - Computerized Medical Imaging and Graphics, 2020 - Elsevier
Quantification of cardiac left ventricle has become a hot topic due to its great significance in
clinical practice. Many efforts have been devoted to LV quantification and obtained …

Deep learning with multi-dimensional medical image data

NT Gessert - 2020 - tore.tuhh.de
In this work, we explore deep learning model design and application in the context of multi-
dimensional data in medical image analysis. A lot of medical image analysis problems come …

Left ventricular parameter regression from deep feature maps of a jointly trained segmentation CNN

S Tilborghs, F Maes - International Workshop on Statistical Atlases and …, 2019 - Springer
Quantification of left ventricular (LV) parameters from cardiac MRI is important to assess
cardiac condition and help in the diagnosis of certain pathologies. We present a CNN-based …

Steerable Pyramid Transform Enables Robust Left Ventricle Quantification

X Zhu, K Ma, W Xue - Chinese Conference on Pattern Recognition and …, 2024 - Springer
Predicting cardiac indices has long been a focal point in the medical imaging community.
While various deep learning models have demonstrated success in quantifying cardiac …