sis 19(23): e6

Research Article

Automated Skin Lesion Detection towards Melanoma

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  • @ARTICLE{10.4108/eai.29-7-2019.159800,
        author={Maryam  Bibi and Anmol  Hamid and Samabia  Tehseen},
        title={Automated Skin Lesion Detection towards Melanoma},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={6},
        number={23},
        publisher={EAI},
        journal_a={SIS},
        year={2019},
        month={8},
        keywords={Skin Cancer, Melanoma, Image Processing, pre-processing, Segmentation, Dermoscopic Images},
        doi={10.4108/eai.29-7-2019.159800}
    }
    
  • Maryam Bibi
    Anmol Hamid
    Samabia Tehseen
    Year: 2019
    Automated Skin Lesion Detection towards Melanoma
    SIS
    EAI
    DOI: 10.4108/eai.29-7-2019.159800
Maryam Bibi1,*, Anmol Hamid1, Samabia Tehseen1
  • 1: Department of computer science, Bahria University Islamabad, Pakistan
*Contact email: maryambb000@gmail.com

Abstract

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.