Wadhawan Tarun, Situ Ning, Rui Hu, Lancaster Keith, Yuan Xiaojing, Zouridakis George
Department of Computer Science, University of Houston, Houston, TX 77204-3058, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:3180-3. doi: 10.1109/IEMBS.2011.6090866.
In this paper we implement the 7-point checklist, a set of dermoscopic criteria widely used by clinicians for melanoma detection, on smart handheld devices, such as the Apple iPhone and iPad. The application developed is using sophisticated image processing and pattern recognition algorithms, yet it is light enough to run on a handheld device with limited memory and computational speed. When combined with a commercially available handheld dermoscope that provides proper lesion illumination, this application provides a truly self-contained handheld system for melanoma detection. Such a device can be used in a clinical setting for routine skin screening, or as an assistive diagnostic device in underserved areas and in developing countries with limited healthcare infrastructure.
在本文中，我们在诸如苹果iPhone和iPad等智能手持设备上实现了7分检查表，这是临床医生广泛用于检测黑色素瘤的一组皮肤镜标准。所开发的应用程序使用了复杂的图像处理和模式识别算法，但它足够轻便，能够在内存和计算速度有限的手持设备上运行。当与提供适当病变照明的商用手持皮肤镜相结合时，该应用程序提供了一个真正独立的用于黑色素瘤检测的手持系统。这样的设备可用于临床环境中的常规皮肤筛查，或作为医疗基础设施有限的欠发达地区和发展中国家的辅助诊断设备。
