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黑素细胞性病变的计算机辅助诊断

Computer-aided diagnosis of melanocytic lesions.

作者信息

Stanganelli Ignazio, Brucale Aldo, Calori Luigi, Gori Roberto, Lovato Alberto, Magi Serena, Kopf Barbara, Bacchilega Roberto, Rapisarda Vincenzo, Testori Alessandro, Ascierto Paolo Antonio, Simeone Ester, Ferri Massimo

机构信息

Skin Cancer Clinic, Center for Cancer Prevention, Viale Randi 5, 48100 Ravenna, Italy.

出版信息

Anticancer Res. 2005 Nov-Dec;25(6C):4577-82.

Abstract

BACKGROUND

The clinical diagnosis of melanoma could be difficult for a general practitioner and, in some cases, for dermatologists. To enhance and support the clinical evaluation of pigmented skin lesions a computer-aided diagnosis has been introduced.

MATERIALS AND METHODS

Images of melanocytic lesions (477 total, 42 melanomas and 435 melanocytic nevi) evaluated in epiluminescence microscopy and recorded with x16 magnification were selected. A training set of 22 melanomas and 218 nevi was randomized from the dataset. The test set was formed by the complement (the remaining 20 melanomas and 217 nevi). Furthermore, a set of images consisting of 31 melanomas and 103 nevi was selected to compare the discrimination capacity of three general practitioners and three dermatologists with experience in dermoscopy (2 years), and with the automatic data analysis for the melanoma early detection system (ADAM). Sensitivity and specificity were estimated for observer assessments and computer diagnosis.

RESULTS

The entire dataset used to test the implementation of the diagnostic algorithms ADAM showed a good sensitivity and specificity performance. Compared with the physicians, the ADAM system showed a slightly higher diagnostic performance in terms of sensitivity and a lower one in terms of specificity. Dermatologists showed higher levels of specificity, but lower levels in terms of sensitivity, when compared with the general practitioners.

CONCLUSION

Image analysis has the potential to distinguish nevi and melanomas and to support the clinical diagnosis of melanocytic lesions by the general practitioner.

摘要

背景

对于全科医生而言,黑色素瘤的临床诊断可能存在困难,在某些情况下,皮肤科医生也会面临同样的问题。为了加强和支持对色素沉着性皮肤病变的临床评估,引入了计算机辅助诊断技术。

材料与方法

选择在落射荧光显微镜下评估并以16倍放大率记录的黑素细胞性病变图像(共477张,其中42例为黑色素瘤,435例为黑素细胞痣)。从数据集中随机抽取22例黑色素瘤和218例痣作为训练集。测试集由其余部分组成(即另外20例黑色素瘤和217例痣)。此外,还选取了一组由31例黑色素瘤和103例痣组成的图像,以比较三名全科医生和三名有皮肤镜检查经验(2年)的皮肤科医生的鉴别能力,以及黑色素瘤早期检测系统(ADAM)的自动数据分析能力。对观察者评估和计算机诊断的敏感性和特异性进行了估计。

结果

用于测试诊断算法ADAM实施情况的整个数据集显示出良好的敏感性和特异性表现。与医生相比,ADAM系统在敏感性方面表现略高,而在特异性方面表现较低。与全科医生相比,皮肤科医生的特异性水平较高,但敏感性水平较低。

结论

图像分析有潜力区分痣和黑色素瘤,并支持全科医生对黑素细胞性病变进行临床诊断。

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