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相关概念视频

Imaging Studies VI: Voiding Cystourethrography and Cystography01:22

Imaging Studies VI: Voiding Cystourethrography and Cystography

15
Voiding Cystourethrography (VCUG) and Cystography are specialized radiographic procedures used to examine the structure and function of the bladder and urethra.Voiding Cystourethrography (VCUG)A Voiding Cystourethrogram (VCUG) is a diagnostic imaging procedure that assesses the anatomy and function of the lower urinary tract. It focuses on the bladder, bladder neck, and urethra, helping detect abnormalities such as vesicoureteral reflux (VUR)—the backward or reverse flow of urine into the...
15
Urinary Bladder01:23

Urinary Bladder

871
The urinary bladder is a hollow, muscular sac that temporarily stores urine before it is expelled from the body. It can hold approximately 600 mL of urine prior to micturition. The bladder is retroperitoneal and located behind the pubic symphysis in the pelvic floor.
In males, the bladder is situated in front of the rectum, while in females, it is positioned anterior to the vagina and uterus. The bladder floor contains an inverted triangular area called the trigone, defined by the two ureteric...
871

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Predictors for Positive Repeated Urine Culture in Patients with Negative Initial Urine Culture before Endoscopic Lithotripsy.

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Large multicenter validation of urine RNA profile for urothelial carcinoma detection and surveillance.

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CystoDS: a multiclass endoscopy image dataset for artificial intelligence-assisted bladder cancer detection.

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Loss of Lean Mass in Rheumatoid Arthritis Is Associated With Loss of Total and Visceral Fat.

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Patient-Reported Symptom Burden Among Thyroid Cancer Survivors: Retrospective Cohort Study.

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Rule-Based Algorithm to Identify Recurrent Non-Hodgkin Lymphoma in Electronic Health Data.

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Bayesian Methods for Subgroup Efficacy and Safety: Application to Japanese Patients in JAVELIN Renal 101.

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相关实验视频

Updated: Jul 15, 2025

Evaluation of Biomaterials for Bladder Augmentation using Cystometric Analyses in Various Rodent Models
10:19

Evaluation of Biomaterials for Bladder Augmentation using Cystometric Analyses in Various Rodent Models

Published on: August 9, 2012

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有效的增强智能框架用于膀损伤检测.

Okyaz Eminaga1,2, Timothy Jiyong Lee3,4, Mark Laurie3,5

  • 1AI Vobis, Palo Alto, CA.

JCO clinical cancer informatics
|September 29, 2023
PubMed
概括
此摘要是机器生成的。

开发人工智能用于膀癌的检测是昂贵的. 这项研究表明,在教育图谱上训练有效的深度学习模型可以实现实时的膀损伤识别.

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Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors
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A Murine Orthotopic Bladder Tumor Model and Tumor Detection System
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相关实验视频

Last Updated: Jul 15, 2025

Evaluation of Biomaterials for Bladder Augmentation using Cystometric Analyses in Various Rodent Models
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Evaluation of Biomaterials for Bladder Augmentation using Cystometric Analyses in Various Rodent Models

Published on: August 9, 2012

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Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors
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Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors

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科学领域:

  • 泌尿器科 泌尿器科 泌尿器科 泌尿器科
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 开发用于膀病变检测的智能系统是昂贵的.
  • 需要有效的策略来创建这些系统.

研究的目的:

  • 评估深度学习模型对于膀病变检测的有效性.
  • 为了确定实时应用的计算效率高的模型.

主要方法:

  • 四个深度学习模型 (ConvNeXt,PlexusNet,MobileNet,SwinTransformer) 在一个教育型囊镜图谱 (312张图像) 上受过训练.
  • 模型在68个囊镜视频上进行了外部验证,其中有病理确认的感兴趣区域 (ROI).
  • 在框架,块和ROI级别上使用特异性和灵敏度来评估性能.

主要成果:

  • 在框架 (30.0%-44.8%) 和块级 (56%-67%) 的模型中,特异性是可比的.
  • 在区块 (100%) 和ROI (100%) 级别的模型中,灵敏度很高.
  • 移动网络和PlexusNet在实时ROI检测方面展示了更高的计算效率.

结论:

  • 一个教育性囊透视图集可以帮助开发智能系统.
  • 有效的深度学习模型有助于创建实时膀病变检测系统.