Maglogiannis Ilias, Doukas Charalampos N
Department of Informatics with Appliances in Biomedicine, University of Central Greece, Lamia 35100, Greece.
IEEE Trans Inf Technol Biomed. 2009 Sep;13(5):721-33. doi: 10.1109/TITB.2009.2017529. Epub 2009 Mar 16.
During the last years, computer-vision-based diagnosis systems have been used in several hospitals and dermatology clinics, aiming mostly at the early detection of skin cancer, and more specifically, the recognition of malignant melanoma tumour. In this paper, we review the state of the art in such systems by first presenting the installation, the visual features used for skin lesion classification, and the methods for defining them. Then, we describe how to extract these features through digital image processing methods, i.e., segmentation, border detection, and color and texture processing, and we present the most prominent techniques for skin lesion classification. The paper reports the statistics and the results of the most important implementations that exist in the literature, while it compares the performance of several classifiers on the specific skin lesion diagnostic problem and discusses the corresponding findings.
在过去几年中,基于计算机视觉的诊断系统已在多家医院和皮肤科诊所使用,主要目的是早期发现皮肤癌,更具体地说是识别恶性黑色素瘤肿瘤。在本文中,我们通过首先介绍此类系统的安装、用于皮肤病变分类的视觉特征以及定义这些特征的方法,来综述其技术现状。然后,我们描述如何通过数字图像处理方法(即分割、边界检测以及颜色和纹理处理)提取这些特征,并介绍皮肤病变分类的最突出技术。本文报告了文献中最重要实施案例的统计数据和结果,同时比较了几种分类器在特定皮肤病变诊断问题上的性能,并讨论了相应的发现。