On the role of texture and color in the classification of dermoscopy images.
This paper addresses the detection of melanoma lesions in dermoscopy images, using texture and color features. Although melanoma detection has been studied in several works, using different types of texture, color and shape features, it is not always clear what is the role of each set of features and which features are most discriminative. This papers aims at clarifying the role of texture and color features. Furthermore, the proposed systems is based on features which can be easily implemented and tested by other researchers. It is concluded that both types of features achieve good detection scores when used alone. The best results (SE=94.1%, SP=77.4%) are achieved by combining them both.
Instituto Superior Tecnico and Institute for Systems and Robotics, Lisbon, Portugal. jsm@isr.ist.utl.pt
Jorge S
JS
Marques
Catarina
C
Barata
Teresa
T
Mendonça
D000465:Algorithms; D003124:Colorimetry / Q000379:methods*; D046169:Dermoscopy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / 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*