Texture, analysis of optical coherence tomography images: feasibility for tissue classification
Texture, analysis of optical coherence tomography images: feasibility for tissue classification
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DOI：
10.1117/1.1577575
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发表时间：
2003-07-01
影响因子：
3.5
通讯作者：
Barton, JK
中科院分区：
文献类型：
--
作者：
Gossage, KW;Tkaczyk, TS;Barton, JK
光学相干层析成像(OCT)通过测量背向反射光来获取组织的横截面图像。来自活体OCT系统的图像通常具有10至15 mm的分辨率，因此最适合于可视化数十至数百微米范围的结构，如组织层或腺体。许多正常和异常组织在这种大小范围内缺乏可见的结构，因此OCT可能不适合于识别这些组织。然而，对结构不良的OCT图像的检查表明，它们经常表现出由于斑点而产生的特征纹理。我们评估了统计和光谱纹理分析技术在根据OCT图像中的结构和斑点含量区分组织类型方面的应用。对于视觉差异较小的图像(小鼠皮肤和脂肪，正确分类率分别为98.5%和97.3%)，对于外观相似的图像(正常和异常小鼠肺，正确分类率分别为64.0和88.6%)，均获得了较好的正确分类率。这项研究表明，OCT图像的纹理分析可能能够区分组织类型，而不依赖于可见的结构。(C)2003年光学仪器工程师学会。
Optical coherence tomography (OCT) acquires cross-sectional images of tissue by measuring back-reflected light. Images from in vivo OCT systems typically have a resolution of 10 to 15 mm, and are thus best suited for visualizing structures in the range of tens to hundreds of microns, such as tissue layers or glands. Many normal and abnormal tissues lack visible structures in this size range, so it may appear that OCT is unsuitable for identification of these tissues. However, examination of structure-poor OCT images reveals that they frequently display a characteristic texture that is due to speckle. We evaluated the application of statistical and spectral texture analysis techniques for differentiating tissue types based on the structural and speckle content in OCT images. Excellent correct classification rates were obtained when images had slight visual differences (mouse skin and fat, correct classification rates of 98.5 and 97.3%, respectively), and reasonable rates were obtained with nearly identical-appearing images (normal versus abnormal mouse lung, correct classification rates of 64.0 and 88.6%, respectively). This study shows that texture analysis of OCT images may be capable of differentiating tissue types without reliance on visible structures. (C) 2003 Society of Photo-Optical Instrumentation Engineers.