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Imaging Studies VI: Voiding Cystourethrography and Cystography01:22

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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...

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Updated: Jun 20, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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使用多视图深度学习技术进行乳房图分类:研究基于图形和变压器的架构.

Francesco Manigrasso1, Rosario Milazzo1, Alessandro Sebastian Russo1

  • 1Politecnico di Torino, Dipartimento di Automatica e Informatica, Corso Duca degli Abruzzi 24, 10129, Turin, Italy.

Medical image analysis
|September 8, 2024
PubMed
概括

深度学习模型对查乳房图片显示出希望,但挑战仍然存在. 基于变压器的架构表现最好,但各种模型的合奏提供了最强大的乳腺癌分类.

关键词:
计算机辅助诊断是一种计算机辅助的诊断.乳房学 乳房学 乳房学视觉变压器 视觉变压器

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科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 放射学 放射学是一门学科.

背景情况:

  • 深度学习 (DL) 提供了自动查乳房影像评估的潜力.
  • 挑战包括低癌症患病率,高分辨率图像和多视图数据集成.
  • 考试级别标签上的弱监督学习受到数据集大小和准确性的限制.

研究的目的:

  • 评估基于变压器和基于图形的新型架构,用于多视图乳房影像.
  • 将它们与最先进的卷积神经网络 (CNN) 进行比较.
  • 在弱监督的环境中评估性能和可解释性.

主要方法:

  • 对变压器 (ViT) 和基于图形的架构进行了广泛的评估.
  • 与CSAW数据集上的多视图CNN进行比较.
  • 在中等规模数据集上使用考试级别标签的低监督培训.

主要成果:

  • 基于变压器的架构展示了卓越的性能.
  • 不同的架构表现出互补的优缺点.
  • 组合多种不同的架构可以比单个模型获得更准确和更强大的结果.

结论:

  • 多视图架构显示了乳腺癌分类的巨大潜力,即使使用了适度的数据集.
  • 基于变压器和图形的模型在整合乳腺扫描视图方面具有优势.
  • 在没有像素级监督或专业网络的情况下,检测小病变仍然具有挑战性.