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Study of Skin Cancer Lesions through Multispectral and 3D Techniques

机译:通过多光谱和3D技术研究皮肤癌病变

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The effective and non-invasive diagnosis of skin cancer is a hot topic in biophotonics since the current gold standard, biopsy followed by histological examination, is a slow and costly procedure for the healthcare system. Therefore, authors have put their efforts in characterizing skin cancer quantitatively through optical and photonic techniques such as 3D topography and multispectral imaging. Skin relief is an important biophysical feature that can be difficult to appreciate by touch, but can be precisely characterized with 3D imaging techniques, such as fringe projection. Color and spectral features given by skin chromophores, which are routinely analyzed by the naked eye and through dermoscopy, can also be quantified by means of multispectral imaging systems. In this study, the outcomes of these two imaging modalities were combined in a machine learning process to enhance classification of melanomas and nevi obtained from the two systems when operating isolately. The results suggest that the combination of 3D and multispectral data is relevant for the medical diagnosis of skin cancer.
机译:皮肤癌的有效和无侵入性诊断是生物学学中的热门话题,因为目前的黄金标准,活组织检查随后是组织学检查,是医疗保健系统的缓慢且昂贵的程序。因此,作者通过光学和光子技术(如3D形貌和多光谱成像)定量地进行了努力。皮肤浮雕是一种重要的生物物理特征,可以通过触摸难以欣赏,但可以精确地表征3D成像技术,例如条纹投影。皮肤发色团给出的颜色和光谱特征,通过肉眼和通过Dermoscopy进行常规分析,也可以通过多光谱成像系统量化。在本研究中,将这两个成像方式的结果组合在机器学习过程中,以增强在分离操作时从两个系统获得的黑色素组和内部的分类。结果表明,3D和多光谱数据的组合与皮肤癌的医学诊断相关。

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