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Hypoplastic left heart syndrome (HLHS) is a congenital heart disease responsible for 23% of infant cardiac deaths each year. HLHS patients are born with an underdeveloped left heart, requiring several surgeries to reconstruct the aorta and…

Patients with hypoplastic left heart syndrome (HLHS) are born with an underdeveloped left heart. They typically receive a sequence of surgeries that result in a single ventricle physiology called the Fontan circulation. While these patients…

Fetal ultrasound screening during pregnancy plays a vital role in the early detection of fetal malformations which have potential long-term health impacts. The level of skill required to diagnose such malformations from live ultrasound…

Left ventricular hypertrophy (LVH) results from chronic remodeling caused by a broad range of systemic and cardiovascular disease including hypertension, aortic stenosis, hypertrophic cardiomyopathy, and cardiac amyloidosis. Early detection…

MOTIVATION: Left ventricular (LV) hypertrophy is a strong predictor of cardiovascular outcomes, but its genetic regulation remains largely unexplained. Conventional phenotyping relies on manual calculation of LV mass and wall thickness, but…

Radiomics, a medical imaging technique, extracts quantitative handcrafted features from images to predict diseases. Harmonization in those features ensures consistent feature extraction across various imaging devices and protocols. Methods…

图像与视频处理 · 电气工程与系统科学 2023-11-23 Jina Lee , Youngtaek Hong , Dawun Jeong , Yeonggul Jang , Jaeik Jeon , Sihyeon Jeong , Taekgeun Jung , Yeonyee E. Yoon , Inki Moon , Seung-Ah Lee , Hyuk-Jae Chang

The deformation of the lateral ventricle (LV) shape is widely studied to identify specific morphometric changes associated with diseases. Since LV enlargement is considered a relative change due to brain atrophy, local longitudinal LV…

图像与视频处理 · 电气工程与系统科学 2024-10-10 Wonjung Park , Suhyun Ahn , Jinah Park

Lateral ventricle (LV) shape analysis holds promise as a biomarker for neurological diseases; however, challenges remain due to substantial shape variability across individuals and segmentation difficulties arising from limited MRI…

计算机视觉与模式识别 · 计算机科学 2025-08-22 Wonjung Park , Suhyun Ahn , Jinah Park

Congenital heart disease is considered as one the most common groups of congenital malformations which affects $6-11$ per $1000$ newborns. In this work, an automated framework for detection of cardiac anomalies during ultrasound screening…

图像与视频处理 · 电气工程与系统科学 2021-09-13 Elisa Chotzoglou , Thomas Day , Jeremy Tan , Jacqueline Matthew , David Lloyd , Reza Razavi , John Simpson , Bernhard Kainz

Two-dimensional echocardiography (2DE) measurements of left ventricle (LV) dimensions are highly significant markers of several cardiovascular diseases. These measurements are often used in clinical care despite suffering from large…

图像与视频处理 · 电气工程与系统科学 2019-11-07 Andrew Gilbert , Marit Holden , Line Eikvil , Svein Arne Aase , Eigil Samset , Kristin McLeod

Understanding the formation, propagation, and breakdown of the main vortex ring (VR) is essential for characterizing left ventricular (LV) hemodynamics, as its dynamics have been linked to the onset and progression of cardiovascular…

流体动力学 · 物理学 2025-07-30 Eneko Lazpita , Michael Neidlin , Jesus Garicano-Mena , Soledad Le Clainche

Objective: Bleeding from gastroesophageal varices (GEV) is a medical emergency associated with high mortality. We aim to construct an artificial intelligence-based model of two-dimensional shear wave elastography (2D-SWE) of the liver and…

Fontan-Associated Liver Disease (FALD) is a disorder arising from hemodynamic changes and venous congestion in the liver. This disease is prominent in patients with hypoplastic left heart syndrome (HLHS). Although HLHS patients typically…

医学物理 · 物理学 2025-11-06 Yaqi Li , Justin D. Weigand , Charles Puelz , Mette S. Olufsen , Alyssa Taylor-LaPole

In cases of pressure or volume overload, probing cardiac function may be difficult because of the interactions between shape and deformations.In this work, we use the LDDMM framework and parallel transport to estimate and reorient…

计算机视觉与模式识别 · 计算机科学 2021-02-18 Nicolas Guigui , Pamela Moceri , Maxime Sermesant , Xavier Pennec

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

Right heart failure (RHF) is a disease characterized by abnormalities in the structure or function of the right ventricle (RV), which is associated with high morbidity and mortality. Lung disease often causes increased right ventricular…

机器学习 · 计算机科学 2025-11-18 Bin Liu , Qinghao Zhao , Yuxi Zhou , Zhejun Sun , Kaijie Lei , Deyun Zhang , Shijia Geng , Shenda Hong

Left ventricular diastolic dysfunction (LVDD) is a group of diseases that adversely affect the passive phase of the cardiac cycle and can lead to heart failure. While left ventricular end-diastolic pressure (LVEDP) is a valuable prognostic…

组织与器官 · 定量生物学 2025-01-23 Emilio A. Mendiola , Raza Rana Mehdi , Dipan J. Shah , Reza Avazmohammadi

Heart transplant patients are followed with periodic right heart catheterizations (RHCs) to identify post-transplant complications and guide treatment. Post-transplant positive outcomes are associated with a steady reduction of right…

Left Ventricular Hypertrophy (LVH) is a major cardiovascular risk factor, linked to heart failure, arrhythmia, and sudden cardiac death, often resulting from chronic stress like hypertension. Electrocardiography (ECG), while varying in…

信号处理 · 电气工程与系统科学 2024-11-14 Wei Tang , Kangning Cui , Raymond H. Chan , Jean-Michel Morel

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 indices, they remain susceptible to mild input perturbations, e.g.,…

图像与视频处理 · 电气工程与系统科学 2024-07-03 Xiangyang Zhu , Kede Ma , Wufeng Xue
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