Schindewolf T, Schiffner R, Stolz W, Albert R, Abmayr W, Harms H
Institute of Virology and Immunology, University of Würzburg, Germany.
J Am Acad Dermatol. 1994 Jul;31(1):33-41. doi: 10.1016/s0190-9622(94)70132-6.
Digital image analysis was found to be a useful technique for improved accuracy of preoperative diagnosis of melanocytic lesions. In previous studies digitized color slides were used as input for digital image analysis. New technologies and smaller video cameras made it possible to develop a camera system that allows the digitization of skin lesions directly from the patient.
We investigated whether conventional color slides or directly digitized images should be used for a reliable recognition of malignant melanoma.
Computer features describing characteristics of the lesions were computed for 404 digitized color slides and for 309 directly acquired lesions. Statistical analysis and classifier construction was performed by the commercial statistical classification program CART.
With the data set derived either from the color slides or from the directly digitized lesions a sensitivity of about 90% for the recognition of malignant melanoma could be obtained.
Both image acquisition techniques allow a reliable detection of malignant melanoma and both are appropriate as input for an image analysis system regarding its efficiency as a diagnostic tool. However, none of the classifiers can be applied with reasonable significance to both techniques.
数字图像分析被发现是一种有助于提高黑素细胞性病变术前诊断准确性的有用技术。在先前的研究中，数字化彩色幻灯片被用作数字图像分析的输入。新技术和小型摄像机使得开发一种能够直接对患者的皮肤病变进行数字化的摄像系统成为可能。
我们研究了应使用传统彩色幻灯片还是直接数字化图像来可靠识别恶性黑色素瘤。
为404张数字化彩色幻灯片和309个直接采集的病变计算描述病变特征的计算机特征。通过商业统计分类程序CART进行统计分析和分类器构建。
使用从彩色幻灯片或直接数字化病变获得的数据集，对于恶性黑色素瘤的识别可获得约90%的敏感性。
两种图像采集技术都能可靠地检测出恶性黑色素瘤，并且就其作为诊断工具的效率而言，两者都适合作为图像分析系统的输入。然而，没有一个分类器能够合理地同时应用于这两种技术。
