Detection of Pigment Networks in Dermoscopy Images

2016 International Conference on Communication, Image and Signal Processing

物理学;无线电电子学;计算机科学

Eltayef, Khalid^1 ; Li, Yongmin^1 ; Liu, Xiaohui^1

Computer Science Department, Brunel University London, Uxbridge

UB8 3PH, United Kingdom^1

关键词: Automatic systems;    Classification process;    Connected component analysis;    Dermoscopy images;    Directional filters;    Pre-processing algorithms;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/787/1/012033/pdf
DOI  :  10.1088/1742-6596/787/1/012033

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

One of the most important structures in dermoscopy images is the pigment network, which is also one of the most challenging and fundamental task for dermatologists in early detection of melanoma. This paper presents an automatic system to detect pigment network from dermoscopy images. The design of the proposed algorithm consists of four stages. First, a pre-processing algorithm is carried out in order to remove the noise and improve the quality of the image. Second, a bank of directional filters and morphological connected component analysis are applied to detect the pigment networks. Third, features are extracted from the detected image, which can be used in the subsequent stage. Fourth, the classification process is performed by applying feed-forward neural network, in order to classify the region as either normal or abnormal skin. The method was tested on a dataset of 200 dermoscopy images from Hospital Pedro Hispano (Matosinhos), and better results were produced compared to previous studies.