Level set initialization based on modified Fuzzy C means thresholding for automated segmentation of skin lesions

Ammara Masood, Adel Ali Al-Jumaily, Yashar Maali

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

7 Citations (Scopus)

Abstract

Segmentation of skin lesion is an important step in the overall automated diagnostic systems used for early detection of skin cancer. Skin lesions can have various different forms which makes segmentation a difficult and complex task. Different methods are present in literature for improving results for skin lesion segmentation. Each method has some pros and cons and it is observed that none of them can be regarded as a generalized method working for all types of skin lesions. The paper proposes an algorithm that combines the advantages of clustering, thresholding and active contour methods currently being used independently for segmentation purposes. A modified algorithm for thresholding based on fusion of Fuzzy C mean clustering and histogram thresholding is applied to initialize level set automatically and also for estimating controlling parameters for level set evolution. The performance of level set segmentation is subject to appropriate initialization, so the proposed algorithm is being compared with some other state-of-the-art initialization methods. The work has been tested on clinical database of 270 images. Parameters for performance evaluation are presented in detail. Increased true detection rate and reduced false positive and false negative errors confirm the effectiveness of the proposed method for skin cancer detection.
Original languageEnglish
Title of host publicationNeural information processing
Subtitle of host publication20th International Conference, ICONIP 2013, Daegu, Korea, November 3-7, 2013 : proceedings, part III
EditorsMinho Lee, Akira Hirose, Zeng-Guang Hou, Rhee Man Kil
PublisherSpringer, Springer Nature
Pages341-351
Number of pages11
ISBN (Print)9783642420504
DOIs
Publication statusPublished - 2013
Externally publishedYes
EventInternational Conference on Neural Information Processing (20th : 2013) - Daegu, Korea
Duration: 3 Nov 20137 Nov 2013

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume8228

Conference

ConferenceInternational Conference on Neural Information Processing (20th : 2013)
CityDaegu, Korea
Period3/11/137/11/13

Keywords

  • Skin cancer
  • Segmentation
  • Diagnosis
  • Thresholding
  • Fuzzy
  • Active contours

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    Masood, A., Al-Jumaily, A. A., & Maali, Y. (2013). Level set initialization based on modified Fuzzy C means thresholding for automated segmentation of skin lesions. In M. Lee, A. Hirose, Z-G. Hou, & R. M. Kil (Eds.), Neural information processing: 20th International Conference, ICONIP 2013, Daegu, Korea, November 3-7, 2013 : proceedings, part III (pp. 341-351). (Lecture Notes in Computer Science; Vol. 8228). Springer, Springer Nature. https://doi.org/10.1007/978-3-642-42051-1_43