作者
Mohamed Attia, Mohammed Hossny, Hailing Zhou, Saeid Nahavandi, Hamed Asadi, Anousha Yazdabadi
发表日期
2019/8/1
期刊
Computer methods and programs in biomedicine
卷号
177
页码范围
17-30
出版商
Elsevier
简介
Background and Objective
Skin melanoma is one of the major health problems in many countries. Dermatologists usually diagnose melanoma by visual inspection of moles. Digital hair removal can provide a non-invasive way to remove hair and hair-like regions as a pre-processing step for skin lesion images. Hair removal has two main steps: hair segmentation and hair gaps inpainting. However, hair segmentation is a challenging task which requires manual tuning of thresholding parameters. Hard-coded threshold leads to over-segmentation (false positives) which in return changes the textural integrity of lesions and or under-segmentation (false negatives) which leaves hair traces and artefacts which affect subsequent diagnosis. Additionally, dermal hair exhibits different characteristics: thin; overlapping; faded; occluded and overlaid on textured lesions.
Methods
In this presented paper, we proposed a deep …
引用总数
201920202021202220232024128755
学术搜索中的文章
M Attia, M Hossny, H Zhou, S Nahavandi, H Asadi… - Computer methods and programs in biomedicine, 2019