Wadhawan Tarun, Situ Ning, Lancaster Keith, Yuan Xiaojing, Zouridakis George
Department of Computer Science, University of Houston, Houston, TX 77204, USA.
Proc IEEE Int Symp Biomed Imaging. 2011 Mar 30;2011:133-136. doi: 10.1109/ISBI.2011.5872372.
We have developed a portable library for automated detection of melanoma termed SkinScan© that can be used on smartphones and other handheld devices. Compared to desktop computers, embedded processors have limited processing speed, memory, and power, but they have the advantage of portability and low cost. In this study we explored the feasibility of running a sophisticated application for automated skin cancer detection on an Apple iPhone 4. Our results demonstrate that the proposed library with the advanced image processing and analysis algorithms has excellent performance on handheld and desktop computers. Therefore, deployment of smartphones as screening devices for skin cancer and other skin diseases can have a significant impact on health care delivery in underserved and remote areas.
我们开发了一个名为SkinScan©的用于自动检测黑色素瘤的便携式库，它可在智能手机和其他手持设备上使用。与台式计算机相比，嵌入式处理器的处理速度、内存和功率有限，但具有便携性和低成本的优势。在本研究中，我们探讨了在苹果iPhone 4上运行用于自动皮肤癌检测的复杂应用程序的可行性。我们的结果表明，所提出的具有先进图像处理和分析算法的库在手持设备和台式计算机上均具有出色的性能。因此，将智能手机用作皮肤癌和其他皮肤疾病的筛查设备，可能会对服务不足和偏远地区的医疗保健服务产生重大影响。
