Jove
Visualize
联系我们

相关概念视频

Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

893
DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
893
Imaging Studies IV: Magnetic Resonance Imaging01:27

Imaging Studies IV: Magnetic Resonance Imaging

427
Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
427

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 journal

Managing the Complexity-Coherence Trade-Off in Clinical Reasoning: A Two-Stage Graph Ontology Based on WHO International Classifications.

Journal of evaluation in clinical practice·2026
Same journal

What Do We Actually Measure? The Epistemic Limits of Surrogate Markers in Chronic Disease.

Journal of evaluation in clinical practice·2026
Same journal

Addressing the How of Implementation: A Hermeneutic Exploration of Implementing Virtual Kidney Care in a Remote, Rural Health Region.

Journal of evaluation in clinical practice·2026
Same journal

Communities of Practice to Develop a Nuanced Understanding of Advanced Generalist Medicine in Junior General Practitioners.

Journal of evaluation in clinical practice·2026
Same journal

The Insight Trap: Recursive Affective-Symbolic Loops and the Architecture of Chronicity.

Journal of evaluation in clinical practice·2026
Same journal

Implicit Bias and Microaggressions in the Care of People With Prolonged Disorders of Consciousness: Bridging Medicine, Disability Studies, and Family Advocacy.

Journal of evaluation in clinical practice·2026
JoVE
x logofacebook logolinkedin logoyoutube logo
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 JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: May 3, 2026

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
06:48

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

8.8K

在3D-MRI图像中多变量脑瘤检测,使用优化细分和统一分类模型.

V Anitha1

  • 1Department of Electronics and Communication Engineering, Sri Muthukumaran Institute of Technology, Chennai, Tamil Nadu, India.

Journal of evaluation in clinical practice
|November 20, 2024
PubMed
概括

这项研究引入了一种新的双步优化的Pyramidal SegNet和3D大脑统一NN,用于改进脑瘤细分和分类. 提出的方法显著减少了细分错误,并提高了3DMRI分析中的检测率.

科学领域:

  • 医疗成像医学成像
  • 人工智能在医学中的应用
  • 神经瘤学神经瘤学

背景情况:

  • 3D磁共振成像 (3D-MRI) 对于脑瘤诊断和治疗计划至关重要.
  • 由于初始轮点提取问题和重叠的组织强度,现有的细分技术难以准确.
  • 脑瘤的准确分类受阻于提取上下文和对称特征的挑战.

研究的目的:

  • 开发一种先进的细分方法,用于精确地定位和划分脑瘤.
  • 提出一种新的分类方法,以提高多变量脑瘤的检测率.
  • 为了最大限度地减少细分错误,提高大脑瘤分析的整体诊断准确度.

主要方法:

  • 一个双步优化的Pyramidal SegNet,具有多尺度对比度卷积注意模块,用于改进对比度和边缘提取.
  • 双步达宁针优化和金字塔级别设置细分与Sobel边缘操作员精确的瘤区域提取.
  • 一个3D大脑统一神经网络 (NN),采用自适应的多层深度统一编码器来提取3D上下文和对称特征.

主要成果:

  • 拟议的细分方法通过避免重叠的组织强度分布,有效地减少错误.
  • 统一的3D大脑NN通过提取关键的3D上下文和对称特征,展示了高的检测率.
  • 在BraTS2020和脑瘤检测2020数据集上进行评估,该模型实现了高精度,回忆和准确性.
关键词:
人工智能 (AI) 是一种人工智能.大脑瘤是个大脑瘤磁共振成像 (MRI) 的使用.优化优化 优化优化细分化 细分化的细分化瘤检测 瘤检测 瘤检测

更多相关视频

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
10:25

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

47.8K
Multicolor 3D Printing of Complex Intracranial Tumors in Neurosurgery
14:15

Multicolor 3D Printing of Complex Intracranial Tumors in Neurosurgery

Published on: January 11, 2020

7.0K

相关实验视频

Last Updated: May 3, 2026

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
06:48

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

8.8K
Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
10:25

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

47.8K
Multicolor 3D Printing of Complex Intracranial Tumors in Neurosurgery
14:15

Multicolor 3D Printing of Complex Intracranial Tumors in Neurosurgery

Published on: January 11, 2020

7.0K

结论:

  • 新的双步优化的Pyramidal SegNet和3D大脑统一的NN显著优于现有的脑瘤细分和分类技术.
  • 拟议的方法提供了更高的精度,回忆和准确性,提高了脑瘤的诊断能力.
  • 这项研究为基于3D-MRI的脑瘤分析提供了更准确,更可靠的强大框架.