Tools for analysing skin properties

恶性黑色素瘤的医学诊断主要通过目视检查进行，因此结果可能是主观和可变的。为了规范诊断实践，我的研究计划侧重于为医疗保健专业人员和公众开发廉价且易于操作的诊断工具，以在早期阶段检测黑色素瘤，以提高生存率。在我之前的NSERC发现资助下，我开发了一系列全自动计算机程序，用于从数字皮肤图像中检测黑色素瘤特异性色素疾病，构建了一个用于测量皮肤表面粗糙度的光学系统，这是专家皮肤科医生用于区分黑色素瘤和某些良性皮肤病的另一个关键诊断特征，并实现了一个痣跟踪计算机系统，该系统通过人类背部的照片监测新的和消失的痣。这些研究工作为规范黑色素瘤检测实践奠定了坚实的基础。在这个发现补助金，我将遵循相同的研究方向，但解决计算机辅助黑色素瘤诊断的其他技术方面。特别是，我将研究以下主题：

Medical diagnosis of malignant melanoma is primarily performed by visual inspection, so that the results can be subjective and variable. In order to standardize the diagnosis practice, my research program focuses on developing inexpensive and easy to operate diagnostic tools for healthcare professionals and the general public to detect melanoma at early stages to improve survival rate. Under my previous NSERC Discovery Grant, I developed a wide range of fully automatic computer programs to detect melanoma-specific pigment disorders from digital skin images, constructed an optic system for measuring skin surface roughness which is another key diagnostic feature used by expert dermatologists to discriminate melanoma from certain benign skin conditions, and implemented a mole tracking computer system which monitors new and disappearing moles over time from photographs of human backs. These research works laid a strong foundation to standardize melanoma detection practice. In this Discovery Grant, I will follow the same research direction, but tackle other technical aspects of computer-aided melanoma diagnosis. In particular, I will investigate following topics: