基于图像处理算法的黑色素瘤早期检测移动应用

Seyed Mohammad Alizadeh, A. Mahloojifar
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引用次数: 9

摘要

黑色素瘤是最危险的皮肤癌,每年导致许多人死亡。然而,早期发现有助于治疗。为了准确检测黑色素瘤,皮肤科医生使用活检,这通常与疼痛、时间和成本有关。随着科技的进步和智能手机的发展,许多移动应用程序已经被设计用于黑色素瘤的早期检测。虽然它们能快速检测黑色素瘤,节省时间和金钱,但它们不如活检准确。本文提出了一种基于Android Studio软件、Java编程语言和OpenCV库的基于图像处理方法和模式识别算法的黑色素瘤早期检测应用。所有检测步骤均使用Android智能手机进行。为了在分类步骤中获得更好的性能,除了智能手机之外,还使用了计算机。该应用程序用户友好,计算出的准确率、灵敏度和特异性平均分别为95%、98%和92.19%。值得注意的是,当病变在几何上不同时,这些结果更可靠。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Mobile Application for Early Detection of Melanoma by Image Processing Algorithms
Melanoma is the most dangerous skin cancer which causes many deaths annually. However, early detection can help treat it. For accurate detection of melanoma, dermatologists use biopsy which is usually associated with pain, time and cost. With the advancement of technology and the development of smartphones, many mobile applications have been designed for early detection of melanoma. Although they are fast in the detection of melanoma and save time and money, they are not as accurate as the biopsy. In this paper, the authors proposed an application for early detection of melanoma using image processing methods and pattern recognition algorithms by Android Studio software, Java programming language, and the OpenCV library. All detection steps were carried out using the Android smartphone. For better performance in the classification step, in addition to the smartphone, a computer was also used. This application is user-friendly and the calculated Accuracy, Sensitivity, and Specificity are 95%, 98%, and 92.19% on average, respectively. It should be noted that these results are more reliable when the lesions are geometrically distinct.
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