title: Automatic detection of blue-white veil by discrete colour matching in dermoscopy images.
abstract: Skin lesions are often comprised of various colours. The presence of multiple colours with an irregular distribution can signal malignancy. Among common colours under dermoscopy, blue-grey (blue-white veil) is a strong indicator of malignant melanoma. Since it is not always easy to visually identify and recognize this feature, a computerised automatic colour analysis method can provide the clinician with an objective second opinion. In this paper, we put forward an innovative method, through colour analysis and computer vision techniques, to automatically detect and segment blue-white veil areas in dermoscopy images. The proposed method is an attempt to mimic the human perception of lesion colours, and improves and outperforms the state-of-the-art as shown in our experiments.
authors: School of Computing Science, Simon Fraser University. amadooei@cs.sfu.ca
authors: Ali
authors: A
authors: Madooei
authors: School of Computing Science, Simon Fraser University.
authors: Mark S
authors: MS
authors: Drew
authors: School of Computing Science, Simon Fraser University.
authors: Maryam
authors: M
authors: Sadeghi
authors: School of Computing Science, Simon Fraser University.
authors: M Stella
authors: MS
authors: Atkins
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003124:Colorimetry / Q000379:methods*; D046169:Dermoscopy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008545:Melanoma / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012878:Skin Neoplasms / Q000473:pathology*