Search research articles

关于 JoVE

概览领导团队博客 JoVE 帮助中心

作者

出版流程编辑委员会范围与政策同行评审常见问题投稿

图书馆员

用户评价订阅访问资源图书馆顾问委员会常见问题

研究

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments 存档

教育

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual 教师资源中心教师网站

使用条款与条件

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序

Same author

Automatic Segmentation of the Left Ventricle Through the Cardiac Cycle in Pediatric Echocardiography Videos Using SegFormer Architecture.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Same author

Socioeconomic determinants of overweight and obesity among Mexican children and adolescents: Systematic review and meta-analysis.

Obesity reviews : an official journal of the International Association for the Study of Obesity·2025

Same author

A Multimodel-Based Screening Framework for C-19 Using Deep Learning-Inspired Data Fusion.

IEEE journal of biomedical and health informatics·2024

Same author

Feature-based 3D+t descriptors of hyperactivated human sperm beat patterns.

Heliyon·2024

Same author

Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention.

Frontiers in radiology·2024

Same author

Efficient Breast Cancer Classification Network with Dual Squeeze and Excitation in Histopathological Images.

Diagnostics (Basel, Switzerland)·2023

Search research articles

相关实验视频

Updated: Jul 12, 2025

Oxygenation-sensitive Cardiac MRI with Vasoactive Breathing Maneuvers for the Non-invasive Assessment of Coronary Microvascular Dysfunction

Oxygenation-sensitive Cardiac MRI with Vasoactive Breathing Maneuvers for the Non-invasive Assessment of Coronary Microvascular Dysfunction

Published on: August 17, 2022

强大的心脏细分被启发式纠正.

Alan Cervantes-Guzmán¹, Kyle McPherson², Jimena Olveres^1,3

¹Facultad de Ingenieria, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico.

|October 27, 2023

概括

此摘要是机器生成的。

这项研究引入了一种基于U-NET的算法,用于准确的心脏细分,改善了对肺高血压等右心脏疾病的早期检测,而无需使用侵入性方法.

更多相关视频

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals

Published on: December 16, 2022

Simultaneous Brightfield, Fluorescence, and Optical Coherence Tomographic Imaging of Contracting Cardiac Trabeculae Ex Vivo

Simultaneous Brightfield, Fluorescence, and Optical Coherence Tomographic Imaging of Contracting Cardiac Trabeculae Ex Vivo

Published on: October 2, 2021

相关实验视频

Last Updated: Jul 12, 2025

Oxygenation-sensitive Cardiac MRI with Vasoactive Breathing Maneuvers for the Non-invasive Assessment of Coronary Microvascular Dysfunction

Oxygenation-sensitive Cardiac MRI with Vasoactive Breathing Maneuvers for the Non-invasive Assessment of Coronary Microvascular Dysfunction

Published on: August 17, 2022

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals

Published on: December 16, 2022

Simultaneous Brightfield, Fluorescence, and Optical Coherence Tomographic Imaging of Contracting Cardiac Trabeculae Ex Vivo

Simultaneous Brightfield, Fluorescence, and Optical Coherence Tomographic Imaging of Contracting Cardiac Trabeculae Ex Vivo

Published on: October 2, 2021

科学领域:

心脏病学心脏病学
医疗成像医学成像
人工智能的人工智能

背景情况:

包括肺高血压在内的右心脏病是全球主要的死亡原因.
当前的医学成像系统在准确细分右心室方面存在困难.
早期发现疾病的非侵入性方法对于避免侵入性手术至关重要.

研究的目的:

开发一个强大的心脏细分算法,以改善对右心脏疾病的早期检测.
为了提高医学心声回声系统的准确性,用于右侧心脏腔细分.
为了减少对诊断的侵入性心脏导管治疗的依赖.

主要方法:

一个基于U-NET架构的算法被开发用于心脏细分.
该模型包含一个圆形检测算法和临床医生指导的后处理改进.
该算法在各种数据集上进行了训练和验证,包括由医疗团队编制的数据集.

主要成果:

拟议的算法实现了与最先进的方法可比的细分精度.
该U-NET模型有效地使用减少训练数据集对所有四个心脏腔进行细分.
后处理步骤显示与手动临床细分的一致性.

结论:

开发的算法为早期检测右心脏病提供了一个有希望的非侵入性方法.
集成专门的检测和后处理步骤显著提高了细分质量.
这种方法有可能提高心血管成像诊断能力.