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Updated: Jun 25, 2025

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计算机断层扫描中的深度学习应用的系统审查和元分析肺癌细分

Ting-Wei Wang¹, Jia-Sheng Hong², Jing-Wen Huang³

¹Institute of Biophotonics, National Yang-Ming Chiao Tung University, Taipei, Taiwan; School of Medicine, National Yang-Ming Chiao Tung University, Taipei, Taiwan.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology

|May 28, 2024

概括

深度学习 (DL) 在CT扫描上显示肺瘤细分的中度准确性,最近的进展提高了性能. 对于不同的临床环境和晚期癌症阶段,需要进一步开发.

科学领域:

医疗成像医学成像
人工智能的人工智能
在瘤学瘤学.

背景情况:

在CT扫描上精确的肺瘤细分对于诊断和治疗至关重要.
深度学习 (DL) 在肺癌细分方面显示出潜在但可变的有效性.
疗效因临床环境和瘤阶段而异.

研究的目的:

进行DL算法对肺癌细分的元分析.
评估整体准确性和影响因素.
评估研究质量并确定需要改进的领域.

主要方法:

在PubMed,Embase和Web of Science的综合文献搜索.
使用CLAIM和QUADAS-2工具进行质量评估.
子相似系数和影响因素的聚合分析.

主要成果:

集成子得分为79%表明中等准确度.
最近的研究 (2022年以后) 显示性能有所改善 (82%).
算法类型,分辨率调整和图像裁剪影响性能.

结论:

DL算法在肺癌细分方面显示出有希望但有效性不同.
在早期肺癌中观察到更高的疗效.
针对不同的临床环境和先进阶段,不断开发定制的DL模型至关重要.

关键词:

图像图像图像图像图像深度学习算法深度学习算法肺癌是一种肺癌.进行元分析分析.分段化分段化分段化分段化

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Computed Tomography

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...