Tools for analysing skin properties

恶性黑色素瘤的医学诊断主要是通过肉眼检查进行的，因此结果可能是主观的和可变的。为了规范诊断实践，我的研究项目专注于为医疗专业人员和普通公众开发廉价且易于操作的诊断工具，以便在早期发现黑色素瘤，以提高存活率。在我之前的NSERC Discovery Grant期间，我开发了一系列全自动计算机程序来从数字皮肤图像中检测黑色素瘤特有的色素紊乱，构建了用于测量皮肤表面粗糙度的光学系统，这是皮肤科专家用来区分黑色素瘤和某些良性皮肤疾病的另一项关键诊断功能，并实现了一个鼹鼠跟踪计算机系统，它可以从人类背部的照片中监测随着时间的推移新生和消失的痣。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。在这项探索基金中，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，我将调查以下主题：

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: