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Based on CT and MRI images acquired from normal pressure hydrocephalus (NPH) patients, using machine learning methods, we aim to establish a multi-modal and high-performance automatic ventricle segmentation method to achieve efficient and…

医学物理 · 物理学 2022-02-02 Xi Zhou , Qinghao Ye , Xiaolin Yang , Jiakuan Chen , Haiqin Ma , Jun Xia , Javier Del Ser , Guang Yang

Purpose: Echocardiography is commonly used as a non-invasive imaging tool in clinical practice for the assessment of cardiac function. However, delineation of the left ventricle is challenging due to the inherent properties of ultrasound…

In the United States, heart disease is the leading cause of death for both men and women, accounting for 610,000 deaths each year [1]. Physicians use Magnetic Resonance Imaging (MRI) scans to take images of the heart in order to…

计算机视觉与模式识别 · 计算机科学 2018-11-22 Ehab Abdelmaguid , Jolene Huang , Sanjay Kenchareddy , Disha Singla , Laura Wilke , Mai H. Nguyen , Ilkay Altintas

A key factor for assessing the state of the heart after myocardial infarction (MI) is to measure whether the myocardium segment is viable after reperfusion or revascularization therapy. Delayed enhancement-MRI or DE-MRI, which is performed…

Segmentation and measurement of cardiac chambers is critical in cardiac ultrasound but is laborious and poorly reproducible. Neural networks can assist, but supervised approaches require the same laborious manual annotations. We built a…

图像与视频处理 · 电气工程与系统科学 2026-02-24 Danielle L. Ferreira , Connor Lau , Zaynaf Salaymang , Rima Arnaout

We introduce EchoXFlow, a clinical echocardiography dataset for learning from ultrasound in its native acquisition geometry rather than from scan-converted Cartesian videos. Existing public datasets offer limited opportunities to study…

计算机视觉与模式识别 · 计算机科学 2026-05-08 Elias Stenhede , Joanna Sulkowska , Eivind Bjørkan Orstad , Henrik Schirmer , Arian Ranjbar

Electrocardiography analysis is widely used in various clinical applications and Deep Learning models for classification tasks are currently in the focus of research. Due to their data-driven character, they bear the potential to handle…

信号处理 · 电气工程与系统科学 2023-07-04 Theresa Bender , Philip Gemke , Ennio Idrobo-Avila , Henning Dathe , Dagmar Krefting , Nicolai Spicher

Temporal echocardiography image registration is a basis for clinical quantifications such as cardiac motion estimation, myocardial strain assessments, and stroke volume quantifications. In past studies, deep learning image registration…

图像与视频处理 · 电气工程与系统科学 2023-09-12 Md. Kamrul Hasan , Haobo Zhu , Guang Yang , Choon Hwai Yap

Color Doppler echocardiography is a widely used non-invasive imaging modality that provides real-time information about the intracardiac blood flow. In an apical long-axis view of the left ventricle, color Doppler is subject to phase…

图像与视频处理 · 电气工程与系统科学 2023-07-06 Hang Jung Ling , Olivier Bernard , Nicolas Ducros , Damien Garcia

In this paper, we propose a new deep learning framework for an automatic myocardial infarction evaluation from clinical information and delayed enhancement-MRI (DE-MRI). The proposed framework addresses two tasks. The first task is…

图像与视频处理 · 电气工程与系统科学 2020-11-02 Kibrom Berihu Girum , Youssef Skandarani , Raabid Hussain , Alexis Bozorg Grayeli , Gilles Créhange , Alain Lalande

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 ejection fraction. In this work, we employ deep learning…

计算机视觉与模式识别 · 计算机科学 2015-12-29 M. R. Avendi , A. Kheradvar , H. Jafarkhani

Left ventricular ejection fraction (LVEF) is a key indicator of cardiac function and plays a central role in the diagnosis and management of cardiovascular disease. Echocardiography, as a readily accessible and non-invasive imaging…

计算机视觉与模式识别 · 计算机科学 2025-12-30 Shravan Saranyan , Pramit Saha

Background: The assessment of left ventricular (LV) function by myocardial perfusion SPECT (MPS) relies on accurate myocardial segmentation. The purpose of this paper is to develop and validate a new method incorporating deep learning with…

图像与视频处理 · 电气工程与系统科学 2023-12-22 Fubao Zhu , Jinyu Zhao , Chen Zhao , Shaojie Tang , Jiaofen Nan , Yanting Li , Zhongqiang Zhao , Jianzhou Shi , Zenghong Chen , Zhixin Jiang , Weihua Zhou

Color Doppler echocardiography is a crucial tool for diagnosing mitral regurgitation (MR). Recent studies have explored intelligent methods for MR diagnosis to minimize user dependence and improve accuracy. However, these approaches often…

计算机视觉与模式识别 · 计算机科学 2025-07-01 Zhe Liu , Yuhao Huang , Lian Liu , Chengrui Zhang , Haotian Lin , Tong Han , Zhiyuan Zhu , Yanlin Chen , Yuerui Chen , Dong Ni , Zhongshan Gou , Xin Yang

Myocardial characterization is essential for patients with myocardial infarction and other myocardial diseases, and the assessment is often performed using cardiac magnetic resonance (CMR) sequences. In this study, we propose a fully…

图像与视频处理 · 电气工程与系统科学 2020-08-19 Xiaoran Zhang , Michelle Noga , Kumaradevan Punithakumar

Left ventricular (LV) function is an important factor in terms of patient management, outcome, and long-term survival of patients with heart disease. The most recently published clinical guidelines for heart failure recognise that over…

Mean aortic pressure (MAP) is a major determinant of perfusion in all organs systems. The ability to forecast MAP would enhance the ability of physicians to estimate prognosis of the patient and assist in early detection of hemodynamic…

机器学习 · 计算机科学 2020-10-20 Eliza Huang , Rui Wang , Uma Chandrasekaran , Rose Yu

Examination of the umbilical artery with Doppler ultrasonography is performed to investigate blood supply to the fetus through the umbilical cord, which is vital for the monitoring of fetal health. Such examination involves several steps…

Non-invasive and cost effective in nature, the echocardiogram allows for a comprehensive assessment of the cardiac musculature and valves. Despite progressive improvements over the decades, the rich temporally resolved data in…

Purpose: To develop and evaluate an end-to-end deep learning pipeline for segmentation and analysis of cardiac magnetic resonance images to provide core-lab processing for a multi-centre registry of Fontan patients. Materials and Methods:…