Pereira, P.M.M., Fonseca-Pinto, R., Pedro Paiv, R., Assuncao, P.A.A., Tavor, L.M.N., Thomaz, L.A. and Faria, S.M.M. (2020) Skin Lesion Classification Enhancement Using Border-Line Features-The Melanoma vs Nevus Problem. Biomedical Signal Processing and Control, 57, Article No. 101765.
https://doi.org/10.1016/j.bspc.2019.101765

has been cited by the following article:

• TITLE: An Intelligent Algorithm for Skin Cancer Detection

  AUTHORS: Amin Nazerzadeh, Afsaneh Nouri Houshyar, Alireza Jahed

  KEYWORDS: Skin Cancer, Malignant, Benign, Image Processing, Log Edge Detector, Segmentation

  JOURNAL NAME: Intelligent Control and Automation, Vol.11 No.1, February 28, 2020

  ABSTRACT: Nowadays, computer vision as an interdisciplinary field is growing in different areas such as medical, electronics, etc. In the field, detection and particularly image segmentation is an essential task in which is difficult to find the appropriate one based on the application. In this paper, a new algorithm is proposed to segment the lesion from background. The algorithm is based on log edge detector with iterative median filtering. We have tested our algorithm on 20 dermoscopic images and compare the lesion detection results with those manually segmented by dermatologists. The experiments represent the effectiveness of proposed algorithm.