Localization of Lesions in Dermoscopy Images Using Ensembles of Thresholding Methods

被引:0
|
作者
Celebi, M. Emre [1 ]
Iyatomi, Hitoshi [2 ]
Schaefer, Gerald [3 ]
Stoecker, William V. [4 ]
机构
[1] Louisiana State Univ, Dept Comp Sci, Shreveport, LA 71105 USA
[2] Hosei Univ, Dept Elect Informat, Tokyo, Japan
[3] Aston Univ, Sch Engn & Appl Sci, Birmingham B4 7ET, W Midlands, England
[4] Stoecker & Assoc, Rolla, MO USA
关键词
PIGMENTED SKIN-LESIONS; EPILUMINESCENCE MICROSCOPY; BORDER DETECTION; ENTROPY; COLOR;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma and other pigmented skin lesions. Due to the difficulty and subjectivity of human interpretation, automated analysis of dermoscopy images has become an important research area. Border detection is often the first step in this analysis. In this article, we present an approximate lesion localization method that serves as a preprocessing step for detecting borders in dermoscopy images. In this method, first the black frame around the image is removed using an iterative algorithm. The approximate location of the lesion is then determined using an ensemble of thresholding algorithms. Experiments on a large set of images demonstrate that the presented method achieves both fast and accurate localization of lesions in dermoscopy images.
引用
收藏
页码:1094 / +
页数:3
相关论文
共 50 条
  • [1] Lesion Border Detection in Dermoscopy Images Using Ensembles of Thresholding Methods
    Celebi, M. Emre
    Wen, Quan
    Hwang, Sae
    Iyatomi, Hitoshi
    Schaefer, Gerald
    SKIN RESEARCH AND TECHNOLOGY, 2013, 19 (01) : E252 - E258
  • [2] Segmentation of skin lesions in dermoscopy images using fuzzy classification of pixels and histogram thresholding
    Luis Garcia-Arroyo, Jose
    Garcia-Zapirain, Begonya
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2019, 168 : 11 - 19
  • [3] Thresholding methods for lesion segmentation of basal cell carcinoma in dermoscopy images
    Kaur, R.
    LeAnder, R.
    Mishra, N. K.
    Hagerty, J. R.
    Kasmi, R.
    Stanley, R. J.
    Celebi, M. E.
    Stoecker, W. V.
    SKIN RESEARCH AND TECHNOLOGY, 2017, 23 (03) : 416 - 428
  • [4] Border detection in dermoscopy images using hybrid thresholding on optimized color channels
    Garnavi, Rahil
    Aldeen, Mohammad
    Celebi, M. Emre
    Varigos, George
    Finch, Sue
    COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 2011, 35 (02) : 105 - 115
  • [5] Automatic Separation of Basal Cell Carcinoma from Benign Lesions in Dermoscopy Images with Border Thresholding Techniques
    Mishra, Nabin K.
    Kaur, Ravneet
    Kasmi, Reda
    Kefel, Serkan
    Guvenc, Pelin
    Cole, Justin G.
    Hagerty, Jason R.
    Aradhyula, Hemanth Y.
    LeAnder, Robert
    Stanley, R. Joe
    Moss, Randy H.
    Stoecker, William V.
    PROCEEDINGS OF THE 12TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2017), VOL 4, 2017, : 115 - 123
  • [6] Deep learning ensembles for melanoma recognition in dermoscopy images
    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)
  • [7] Approximate lesion localization in dermoscopy images
    Celebi, M. Emre
    Iyatomi, Hitoshi
    Schaefer, Gerald
    Stoecker, William V.
    SKIN RESEARCH AND TECHNOLOGY, 2009, 15 (03) : 314 - 322
  • [8] Global versus Hybrid Thresholding for Border Detection in Dermoscopy Images
    Garnavi, Rahil
    Aldeen, Mohammad
    Finch, Sue
    Varigos, George
    IMAGE AND SIGNAL PROCESSING, PROCEEDINGS, 2010, 6134 : 531 - +
  • [9] Analyzing Skin Lesions in Dermoscopy Images Using Convolutional Neural Networks
    Singh, Vatsala
    Nwogu, Ifeoma
    2018 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2018, : 4035 - 4040
  • [10] Automatic segmentation of dermoscopy images using saliency combined with adaptive thresholding based on wavelet transform
    Kai Hu
    Si Liu
    Yuan Zhang
    Chunhong Cao
    Fen Xiao
    Wei Huang
    Xieping Gao
    Multimedia Tools and Applications, 2020, 79 : 14625 - 14642