Automated Skin Lesion Detection towards Melanoma

被引:3
作者
Bibi, Maryam [1 ]
Hamid, Anmol [1 ]
Tehseen, Samabia [1 ]
机构
[1] Bahria Univ Islamabad, Dept Comp Sci, Islamabad, Pakistan
关键词
Skin Cancer; Melanoma; Image Processing; pre-processing; Segmentation; Dermoscopic Images; SEGMENTATION;
D O I
10.4108/eai.29-7-2019.159800
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Skin cancer melanoma is one of the most dangerous cancers in the world. It is crucial to diagnose it in initial phases before it invades other organs. However, it requires an efficient and reliable diagnostic computer aided system for early detection.In this research study we aim to detect the skin cancer from two different image datasets. We also present the solution for images that contain disk objects. In initial phase we perform pre-processing, which is followed by segmentation phase.Then candidate dataset is evaluated using different measures such as accuracy, specificity, sensitivity and similarity.Obtained results are compared with results of techniques used in academic literature. We claim that our techniques give better accuracy for cancer detection.
引用
收藏
页码:1 / 9
页数:9
相关论文
共 30 条
[1]  
Abuzaghleh O., 2014, SYST APPL TECHN C LI
[2]   Noninvasive Real-Time Automated Skin Lesion Analysis System for Melanoma Early Detection and Prevention [J].
Abuzaghleh, Omar ;
Barkana, Buket D. ;
Faezipour, Miad .
IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE, 2015, 3
[3]   Saliency-Based Lesion Segmentation Via Background Detection in Dermoscopic Images [J].
Ahn, Euijoon ;
Kim, Jinman ;
Bi, Lei ;
Kumar, Ashnil ;
Li, Changyang ;
Fulham, Michael ;
Feng, David Dagan .
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2017, 21 (06) :1685-1693
[4]  
Al-Amri SS, 2010, INT J COMPUT SCI NET, V10, P139
[5]  
[Anonymous], 2016, ARXIV PREPRINT ARXIV
[6]  
[Anonymous], 2019, B ELECT ENG INFORM
[7]   Automatic rat brain segmentation from MRI using statistical shape models and random forest [J].
Bendazzoli, Simone ;
Brusini, Irene ;
Damberg, Peter ;
Smedby, Orjan ;
Andersson, Leif ;
Wang, Chunliang .
MEDICAL IMAGING 2019: IMAGE PROCESSING, 2019, 10949
[8]   Deep learning ensembles for melanoma recognition in dermoscopy images [J].
Codella, N. C. F. ;
Nguyen, Q. -B. ;
Pankanti, S. ;
Gutman, D. A. ;
Helba, B. ;
Halpern, A. C. ;
Smith, J. R. .
IBM JOURNAL OF RESEARCH AND DEVELOPMENT, 2017, 61 (4-5)
[9]  
Dutta Atrayee, 2019, 2019 International Conference on Communication and Signal Processing (ICCSP), P0315, DOI 10.1109/ICCSP.2019.8698033
[10]  
Garnavi R., 2012, INT J BIOL LIFE SCI, V8, P126