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Raman spectroscopy for human cancer tissue diagnosis: A pattern recognition approach

机译:用于人类癌症组织诊断的拉曼光谱:一种模式识别方法

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In this work, optical scattering using Raman spectroscopy has been analyzed for various cancer tissues. The Raman shifts obtained at the Indiana University Bloomington (IUB) and Indiana University-Purdue University Indianapolis (IUPUI) laboratories have been processed for diagnosing various types of cancer tissues. The objective of this research is to distinguish between cancerous and non-cancerous tissues. Small size tissue samples have been processed, seeking the minimum size tissue that can be diagnosed via Raman spectroscopy. The tests have been conducted on nearly 20 human tissues. A Matlab program has been written following Parzen-Window classifier to recognize the Raman shift pattern for various types of cancer tissues, including breast cancer, kidney, and Gyn-Uterus. A software visual model has been used for data processing. Unique signals for breast and kidney tumors have been obtained. The approach followed in this paper shows promise for early cancer detection in humans.
机译:在这项工作中,已经分析了使用拉曼光谱的光学散射对各种癌症组织的影响。在印第安纳大学布卢明顿分校(IUB)和印第安纳大学普渡大学印第安纳波利斯分校(IUPUI)实验室获得的拉曼位移已用于诊断各种类型的癌症组织。这项研究的目的是区分癌性组织和非癌性组织。小尺寸的组织样本已经过处理,寻求可以通过拉曼光谱法诊断的最小尺寸的组织。该测试已在近20个人体组织上进行。在Parzen-Window分类器之后编写了一个Matlab程序,以识别各种类型的癌组织(包括乳腺癌,肾癌和妇幼子宫)的拉曼位移模式。软件可视模型已用于数据处理。已经获得了乳腺和肾脏肿瘤的独特信号。本文采用的方法显示出有望在人类中早期发现癌症。

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