Technical University of Catalonia, Centre for Sensors, Instruments and Systems Development (CD6), Terrassa, Spain.
Hospital Clínic i Provincial de Barcelona, Barcelona, Spain.
J Biomed Opt. 2017 Jun 1;22(6):65006. doi: 10.1117/1.JBO.22.6.065006.
This article proposes a multispectral system that uses the analysis of the spatial distribution of color and spectral features to improve the detection of skin cancer lesions, specifically melanomas and basal cell carcinomas. The system consists of a digital camera and light-emitting diodes of eight different wavelengths (414 to 995 nm). The parameters based on spectral features of the lesions such as reflectance and color, as well as others empirically computed using reflectance values, were calculated pixel-by-pixel from the images obtained. Statistical descriptors were calculated for every segmented lesion [mean ( x ˜ ), standard deviation ( σ ), minimum, and maximum]; descriptors based on the first-order statistics of the histogram [entropy ( E p ), energy ( E n ), and third central moment ( μ 3 )] were also obtained. The study analyzed 429 pigmented and nonpigmented lesions: 290 nevi and 139 malignant (95 melanomas and 44 basal cell carcinomas), which were split into training and validation sets. Fifteen parameters were found to provide the best sensitivity (87.2% melanomas and 100% basal cell carcinomas) and specificity (54.5%). The results suggest that the extraction of textural information can contribute to the diagnosis of melanomas and basal cell carcinomas as a supporting tool to dermoscopy and confocal microscopy.
本文提出了一种多光谱系统，该系统利用颜色和光谱特征的空间分布分析来提高皮肤癌病变（特别是黑素瘤和基底细胞癌）的检测能力。该系统由一个数码相机和 8 个不同波长（414 到 995nm）的发光二极管组成。根据病变的光谱特征（如反射率和颜色）以及其他基于反射率值计算的经验参数，对获得的图像逐像素进行计算。对每个分割的病变计算统计描述符[平均值 ( x ˜ )、标准差 ( σ )、最小值和最大值]；还获得了基于直方图一阶统计的描述符[熵 ( E p )、能量 ( E n )和第三中心矩 ( μ 3 )]。该研究分析了 429 个色素性和非色素性病变：290 个痣和 139 个恶性病变（95 个黑素瘤和 44 个基底细胞癌），这些病变被分为训练集和验证集。发现 15 个参数可提供最佳的敏感性（87.2%的黑素瘤和 100%的基底细胞癌）和特异性（54.5%）。结果表明，纹理信息的提取可以作为皮肤镜和共聚焦显微镜的辅助工具，有助于黑素瘤和基底细胞癌的诊断。
