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首页> 外文会议>BMEI 2012;International Conference on Biomedical Engineering and Informatics >Hyperspectral imaging and spectral-spatial classification for cancer detection
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Hyperspectral imaging and spectral-spatial classification for cancer detection

机译：高光谱成像和光谱空间分类用于癌症检测

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Hyperspectral imaging is an emerging technology for biomedical applications. In this study, an advanced image processing and classification method is proposed to analyze hyperspectral image data for prostate cancer detection. Least squares support vector machines (LS-SVMs) were developed and evaluated for classifying hyperspectral data in order to enhance the detection of cancer tissue. The method was used to detect prostate cancer in tumor-bearing mice. Spatially resolved images were created to highlight the differences of the reflectance properties of cancer versus those of normal tissue. Preliminary results in mice show that the hyperspectral imaging and classification method was able to reliably detect prostate tumors in the animal model. The hyperspectral imaging technique may provide a new tool for optical diagnosis of cancer.
机译：高光谱成像是一种用于生物医学应用的新兴技术。在这项研究中，提出了一种先进的图像处理和分类方法来分析高光谱图像数据以检测前列腺癌。开发了最小二乘支持向量机（LS-SVM）并进行了评估，以对高光谱数据进行分类，以增强对癌症组织的检测。该方法用于检测荷瘤小鼠的前列腺癌。创建空间分辨图像以突出显示癌症与正常组织的反射特性之间的差异。小鼠的初步结果表明，高光谱成像和分类方法能够可靠地检测动物模型中的前列腺肿瘤。高光谱成像技术可以为光学诊断癌症提供新的工具。

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