Deformable medical image registration: A survey
Deformable image registration is a fundamental task in medical image processing. Among
its most important applications, one may cite: 1) multi-modality fusion, where information …
its most important applications, one may cite: 1) multi-modality fusion, where information …
A review of heart chamber segmentation for structural and functional analysis using cardiac magnetic resonance imaging
Cardiovascular magnetic resonance (CMR) has become a key imaging modality in clinical
cardiology practice due to its unique capabilities for non-invasive imaging of the cardiac …
cardiology practice due to its unique capabilities for non-invasive imaging of the cardiac …
3D deeply supervised network for automated segmentation of volumetric medical images
While deep convolutional neural networks (CNNs) have achieved remarkable success in 2D
medical image segmentation, it is still a difficult task for CNNs to segment important organs …
medical image segmentation, it is still a difficult task for CNNs to segment important organs …
A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI
Segmentation of the left ventricle (LV) from cardiac magnetic resonance imaging (MRI)
datasets is an essential step for calculation of clinical indices such as ventricular volume and …
datasets is an essential step for calculation of clinical indices such as ventricular volume and …
Fully convolutional multi-scale residual DenseNets for cardiac segmentation and automated cardiac diagnosis using ensemble of classifiers
Deep fully convolutional neural network (FCN) based architectures have shown great
potential in medical image segmentation. However, such architectures usually have millions …
potential in medical image segmentation. However, such architectures usually have millions …
Deep learning–based method for fully automatic quantification of left ventricle function from cine MR images: a multivendor, multicenter study
Q Tao, W Yan, Y Wang, EHM Paiman, DP Shamonin… - Radiology, 2019 - pubs.rsna.org
Purpose To develop a deep learning–based method for fully automated quantification of left
ventricular (LV) function from short-axis cine MR images and to evaluate its performance in a …
ventricular (LV) function from short-axis cine MR images and to evaluate its performance in a …
A review of segmentation methods in short axis cardiac MR images
For the last 15 years, Magnetic Resonance Imaging (MRI) has become a reference
examination for cardiac morphology, function and perfusion in humans. Yet, due to the …
examination for cardiac morphology, function and perfusion in humans. Yet, due to the …
Ultrasound image segmentation: a survey
This paper reviews ultrasound segmentation methods, in a broad sense, focusing on
techniques developed for medical B-mode ultrasound images. First, we present a review of …
techniques developed for medical B-mode ultrasound images. First, we present a review of …
Four-chamber heart modeling and automatic segmentation for 3-D cardiac CT volumes using marginal space learning and steerable features
We propose an automatic four-chamber heart segmentation system for the quantitative
functional analysis of the heart from cardiac computed tomography (CT) volumes. Two topics …
functional analysis of the heart from cardiac computed tomography (CT) volumes. Two topics …
Micro-CT of rodents: state-of-the-art and future perspectives
Micron-scale computed tomography (micro-CT) is an essential tool for phenoty** and for
elucidating diseases and their therapies. This work is focused on preclinical micro-CT …
elucidating diseases and their therapies. This work is focused on preclinical micro-CT …