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Hyperspectral imaging and spectral classification for assisting in vivo diagnosis of melanoma precursors: preliminary results obtained from mice

机译:高光谱成像和光谱分类有助于黑色素瘤前体的体内诊断:从小鼠获得的初步结果

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Dysplastic nevi are at high risk of converting to melanoma. Early detection of signs of skin dysplasias at their curable stage, is crucial. We present an integrated system combining a Hyperspectral Camera system (HyCam), with spectral classification algorithms, developed for the in vivo and objective discrimination between non dysplastic, dysplastic nevi and melanomas. A melanoma animal model was developed in order to monitor the process of melanoma development. Reference spectra were collected from normal skin areas, which were compared with the spectra obtained from the lesions using the Spectral Angle Mapper (SAM) algorithm. A pseoudocolor map was created with different colors representing various degrees of similarity between test and reference spectra. The system's predictions ware validated with biopsy/histology. Both sensitivity and specificity were found to be 77%, highlighting the potential of the method to improve diagnostic and screening accuracies.
机译:发育不良痣极易转化为黑色素瘤。至关重要的是及早发现皮肤不典型增生的迹象。我们提出了一种结合了高光谱相机系统(HyCam)和光谱分类算法的集成系统,该系统是为非增生性,增生性痣和黑色素瘤之间的体内和客观鉴别而开发的。为了监测黑色素瘤发展过程,开发了黑色素瘤动物模型。从正常皮肤区域收集参考光谱,将其与使用光谱角度映射器(SAM)算法从病变获得的光谱进行比较。用不同的颜色创建伪彩色图,代表测试光谱和参考光谱之间的相似程度。该系统的预测软件已通过活检/组织学验证。发现灵敏度和特异性均为77%,突出了该方法改善诊断和筛查准确性的潜力。

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