折射率作为脑病变有效诊断参数的独特性:一种应用费曼方程预测CT-MR融合图像折射率的无创新技术

T. Biswas, S. Ramadan, S. Ghosh, Rabi N. Bhattacharya
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引用次数: 2

摘要

目的-折射率(RI)是组织的一种独特的物理性质。由于组织谷胱甘肽浓度的消耗改变了电子密度,它在肿瘤和脑炎症条件下发生变化。本研究的目的是通过无创的CT-MR融合图像来预测脑病变的RI值。材料与方法:采用刚性配准技术,将CT与MR图像结合生成ctmr融合图像,准确检测病变。独立分量分析确定组织图像的颜色值和灰度值。然后神经网络软件使用这些值生成CT-MR融合图像的颜色映射。利用CT图像的电子密度和彩色图像的光学频率,应用Feynman方程确定RI值。在实验室测定相应活检标本的RI值和谷胱甘肽水平。——结果。彩色CT-MR融合图像显示组织的真实颜色。图像确定的RI值与活检确定的RI值一致。在1.353 ~ 1.359之间为良性,在1.412以上为恶性。结论彩色CT-MR融合图像预测RI值可提高诊断准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Uniqueness Of Refractive Index As An Effective Diagnostic Parameter For Brain Lesions: A Novel Noninvasive Technique To Predict Refractive Index From CT-MR Fusion Image By Applying Feynman’s Equation
PURPOSE – The refractive index (RI) is a unique physical property of tissue. It changes in neoplastic and inflammatory condition of brain due to depletion of tissue glutathione concentration changing the electron density. The purpose of the study was to predict RI value of the brain lesions from the CT-MR fused images non invasively. MATERIALS AND METHODS –CTMR fusion image was produced by combining CT and MR images by rigid registration technique to detect the pathology accurately. Independent component analysis determines the color value and gray value of the images of the tissue. These values were then used by Neural Network software to generate a color mapping of the CT-MR fusion image. Electron density derived from CT images and optical frequency from color image were used to determine RI value by applying Feynman’s equation. RI value and glutathione levels of corresponding biopsy specimens were determined in the laboratory. RESULTS –.A colored CT-MR fusion image shows true color of the tissue. The RI values determined from images were in agreement with biopsy determined RI values. Values between 1.353 through 1.359 are benign and RI value above 1.412 were found malignant.CONCLUSIONPredicting RI value using colored CT-MR fused images will increase diagnostic accuracy.
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