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相关论文: Automated cardiovascular magnetic resonance image …

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Cardiovascular magnetic resonance (CMR) imaging is the gold standard for diagnosing several heart diseases due to its non-invasive nature and proper contrast. MR imaging is time-consuming because of signal acquisition and image formation…

图像与视频处理 · 电气工程与系统科学 2025-04-29 Kian Anvari Hamedani , Narges Razizadeh , Shahabedin Nabavi , Mohsen Ebrahimi Moghaddam

Large prospective epidemiological studies acquire cardiovascular magnetic resonance (CMR) images for pre-symptomatic populations and follow these over time. To support this approach, fully automatic large-scale 3D analysis is essential. In…

图像与视频处理 · 电气工程与系统科学 2019-07-04 Rahman Attar , Marco Pereanez , Christopher Bowles , Stefan K. Piechnik , Stefan Neubauer , Steffen E. Petersen , Alejandro F. Frangi

Magnetic resonance imaging (MRI) is a widely known medical imaging technique used to assess the heart function. Deep learning (DL) models perform several tasks in cardiac MRI (CMR) images with good efficacy, such as segmentation,…

图像与视频处理 · 电气工程与系统科学 2022-05-03 Daniel Lima , Catharine Graves , Marco Gutierrez , Bruno Brandoli , Jose Rodrigues-Jr

Cardiac magnetic resonance imaging (MRI) is a pivotal tool for assessing cardiac function. Precise segmentation of cardiac structures is imperative for accurate cardiac functional evaluation. This paper introduces a semi-supervised model…

图像与视频处理 · 电气工程与系统科学 2024-05-24 Hejun Huang , Zuguo Chen , Yi Huang , Guangqiang Luo , Chaoyang Chen , Youzhi Song

Cardiac Magnetic Resonance (CMR) is the most effective tool for the assessment and diagnosis of a heart condition, which malfunction is the world's leading cause of death. Software tools leveraging Artificial Intelligence already enhance…

计算机视觉与模式识别 · 计算机科学 2021-03-16 Adrianna Janik , Jonathan Dodd , Georgiana Ifrim , Kris Sankaran , Kathleen Curran

Coronary artery disease (CAD) is the most common cause of death globally, and its diagnosis is usually based on manual myocardial segmentation of Magnetic Resonance Imaging (MRI) sequences. As the manual segmentation is tedious,…

图像与视频处理 · 电气工程与系统科学 2023-02-27 Yutian Chen , Xiaowei Xu , Dewen Zeng , Yiyu Shi , Haiyun Yuan , Jian Zhuang , Yuhao Dong , Qianjun Jia , Meiping Huang

In this paper, we develop a 2D and 3D segmentation pipelines for fully automated cardiac MR image segmentation using Deep Convolutional Neural Networks (CNN). Our models are trained end-to-end from scratch using the ACD Challenge 2017…

计算机视觉与模式识别 · 计算机科学 2017-08-01 Jay Patravali , Shubham Jain , Sasank Chilamkurthy

Myocardial Velocity Mapping Cardiac MR (MVM-CMR) can be used to measure global and regional myocardial velocities with proved reproducibility. Accurate left ventricle delineation is a prerequisite for robust and reproducible myocardial…

图像与视频处理 · 电气工程与系统科学 2021-04-28 Mengmeng Kuang , Yinzhe Wu , Diego Alonso-Álvarez , David Firmin , Jennifer Keegan , Peter Gatehouse , Guang Yang

Cardiovascular disease (CVD) is the leading cause of mortality yet largely preventable, but the key to prevention is to identify at-risk individuals before adverse events. For predicting individual CVD risk, carotid intima-media thickness…

计算机视觉与模式识别 · 计算机科学 2017-06-05 Jae Y. Shin , Nima Tajbakhsh , R. Todd Hurst , Christopher B. Kendall , Jianming Liang

We propose an automatic method using dilated convolutional neural networks (CNNs) for segmentation of the myocardium and blood pool in cardiovascular MR (CMR) of patients with congenital heart disease (CHD). Ten training and ten test CMR…

计算机视觉与模式识别 · 计算机科学 2017-04-13 Jelmer M. Wolterink , Tim Leiner , Max A. Viergever , Ivana Išgum

Accurate segmentation of the heart is an important step towards evaluating cardiac function. In this paper, we present a fully automated framework for segmentation of the left (LV) and right (RV) ventricular cavities and the myocardium…

计算机视觉与模式识别 · 计算机科学 2017-10-11 Christian F. Baumgartner , Lisa M. Koch , Marc Pollefeys , Ender Konukoglu

Three-dimensional cine-MRI is of crucial importance for assessing the cardiac function. Features that describe the anatomy and function of cardiac structures (e.g. Left Ventricle (LV), Right Ventricle (RV), and Myocardium(MC)) are known to…

计算机视觉与模式识别 · 计算机科学 2017-09-12 M. Hossein Eybposh , Mohammad Haghir Ebrahim-Abadi , Mohammad Jalilpour-Monesi , Seyed Saman Saboksayr

Cardiac magnetic resonance imaging (CMR), considered the gold standard for noninvasive cardiac assessment, is a diverse and complex modality requiring a wide variety of image processing tasks for comprehensive assessment of cardiac…

图像与视频处理 · 电气工程与系统科学 2025-12-03 Athira J Jacob , Indraneel Borgohain , Teodora Chitiboi , Puneet Sharma , Dorin Comaniciu , Daniel Rueckert

The morphological structure of left ventricle segmented from cardiac magnetic resonance images can be used to calculate key clinical parameters, and it is of great significance to the accurate and efficient diagnosis of cardiovascular…

计算机视觉与模式识别 · 计算机科学 2018-09-28 Han Kang , Defeng Chen

Cardiovascular magnetic resonance (CMR) is the gold standard for assessing cardiac function, but individual cardiac cycles complicate automatic temporal comparison or sub-phase analysis. Accurate cardiac keyframe detection can eliminate…

Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a limitation of CMR is its slow imaging speed, which causes patient discomfort and introduces artifacts in the images. There…

Left ventricular (LV) volumes estimation is a critical procedure for cardiac disease diagnosis. The objective of this paper is to address direct LV volumes prediction task. Methods: In this paper, we propose a direct volumes prediction…

计算机视觉与模式识别 · 计算机科学 2018-04-10 Gongning Luo , Suyu Dong , Kuanquan Wang , Wangmeng Zuo , Shaodong Cao , Henggui Zhang

Background: Conventional cardiovascular magnetic resonance (CMR) in paediatric and congenital heart disease uses 2D, breath-hold, balanced steady state free precession (bSSFP) cine imaging for assessment of function and cardiac-gated,…

图像与视频处理 · 电气工程与系统科学 2025-07-01 Mark Wrobel , Michele Pascale , Tina Yao , Ruaraidh Campbell , Elena Milano , Michael Quail , Jennifer Steeden , Vivek Muthurangu