数字图像中可计算图像纹理特征的影响因素和稳定性的评估
Diego Andrade1, Howard C Gifford1, Mini Das1,2,3
1Department of Biomedical Engineering, University of Houston, 4800 Calhoun Rd, Houston, TX 77004, USA.
Tomography (Ann Arbor, Mich.)
|August 27, 2025
概括
量子化对医学成像中的纹理分析有很大的影响. 一种新的规范化方法减少了纹理大小的变化,提高了使用放射学的人工智能和个性化医学应用的稳定性.
科学领域:
- 医学成像
- 辐射学
- 人工智能 (AI)
背景情况:
- 在医疗图像中提取隐藏信息时,
- 放射学,人工智能和个性化医疗旨在获得患者特定的数据,同时尽量减少系统的变化.
- 数字乳房图解 (DBT) 被用作模型,但研究结果适用于广泛.
研究的目的:
- 为了研究影响纹理估计的因素,特别是Haralick的灰色水平共发生矩阵 (GLCM) 特性.
- 在不同的成像系统和处理技术中确定减少纹理特征大小的方法.
主要方法:
- 检查的纹理估计参数:量化,像素距离偏移和感兴趣区域 (ROI) 大小.
- 开发并应用了一种新的多分辨率规范化技术.
- 使用模拟和临床DBT图像验证结果.
主要成果:
- 量化被确定为影响GLCM大小和值范围的最有影响的参数.
- 拟议的多分辨率规范化显著减少了纹理大小差异 (例如,在8-128个量子化之间为7.34%).
- 由于后处理过器和估计变量 (补偿,投资回报率) 的变化被量化.
结论:
- 后处理 (如过器) 和估计变量之间的差异会导致显著的纹理大小变化.
- 开发的标准化增强了对估计方法变化的稳定性.
- 这种方法提高了对患者特定信息的敏感性,
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