Approximate lesion localization in dermoscopy images.

M Emre Celebi, Hitoshi Iyatomi, Gerald Schaefer, William V Stoecker
Author Information
  1. M Emre Celebi: Department of Computer Science, Louisiana State University, Technology Center 206, One University Place, Shreveport, LA 71115, USA. ecelebi@Isus.edu

Abstract

BACKGROUND: Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma and other pigmented skin lesions. Because of 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.
METHODS: 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.
RESULTS: The method is tested on a set of 428 dermoscopy images. The localization error is quantified by a metric that uses dermatologist-determined borders as the ground truth.
CONCLUSION: The results demonstrate that the method presented here achieves both fast and accurate localization of lesions in dermoscopy images.

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Grants

  1. R44 CA101639/NCI NIH HHS
  2. R44 CA101639-02A2/NCI NIH HHS
  3. 2R44 CA-101639-02A2/NCI NIH HHS

MeSH Term

Algorithms
Artificial Intelligence
Dermoscopy
Humans
Image Enhancement
Image Interpretation, Computer-Assisted
Pattern Recognition, Automated
Reproducibility of Results
Sensitivity and Specificity
Skin Neoplasms

Word Cloud

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