title: Incorporating Colour Information for Computer-Aided Diagnosis of Melanoma from Dermoscopy Images: A Retrospective Survey and Critical Analysis.
abstract: Cutaneous melanoma is the most life-threatening form of skin cancer. Although advanced melanoma is often considered as incurable, if detected and excised early, the prognosis is promising. Today, clinicians use computer vision in an increasing number of applications to aid early detection of melanoma through dermatological image analysis (dermoscopy images, in particular). Colour assessment is essential for the clinical diagnosis of skin cancers. Due to this diagnostic importance, many studies have either focused on or employed colour features as a constituent part of their skin lesion analysis systems. These studies range from using low-level colour features, such as simple statistical measures of colours occurring in the lesion, to availing themselves of high-level semantic features such as the presence of blue-white veil, globules, or colour variegation in the lesion. This paper provides a retrospective survey and critical analysis of contributions in this research direction.
authors.affiliation: School of Computing Science, Simon Fraser University, Burnaby, BC, Canada.
authors.forename: Ali
authors.identifier: 0000-0003-3240-5179
authors.initials: A
authors.lastname: Madooei
authors.affiliation: School of Computing Science, Simon Fraser University, Burnaby, BC, Canada.
authors.forename: Mark S
authors.initials: MS
authors.lastname: Drew