Melanoma detection using delaunay triangulation

A. Pennisi, D. D. Bloisi, D. Nardi, A. R. Giampetruzzi, C. Mondino, A. Facchiano

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

9 Citations (Scopus)

Abstract

The detection of malignant lesions in dermoscopic images by using automatic diagnostic tools can help in reducing mortality from melanoma. In this paper, we describe a fully-automatic algorithm for skin lesion segmentation in dermoscopic images. The proposed approach is highly accurate when dealing with benign lesions, while the detection accuracy significantly decreases when melanoma images are segmented. This particular behavior lead us to consider geometrical and color features extracted from the output of our algorithm for classifying melanoma images, achieving promising results.

Original languageEnglish
Title of host publicationProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
PublisherIEEE Computer Society
Pages791-798
Number of pages8
Volume2016-January
ISBN (Print)9781509001637
DOIs
Publication statusPublished - Jan 4 2016
Event27th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2015 - Vietri sul Mare, Salerno, Italy
Duration: Nov 9 2015Nov 11 2015

Other

Other27th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2015
CountryItaly
CityVietri sul Mare, Salerno
Period11/9/1511/11/15

Fingerprint

Triangulation
Skin
Color

Keywords

  • Automatic segmentation
  • Border detection
  • Dermoscopy images
  • Melanoma detection

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Computer Science Applications

Cite this

Pennisi, A., Bloisi, D. D., Nardi, D., Giampetruzzi, A. R., Mondino, C., & Facchiano, A. (2016). Melanoma detection using delaunay triangulation. In Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI (Vol. 2016-January, pp. 791-798). [7372213] IEEE Computer Society. https://doi.org/10.1109/ICTAI.2015.117

Melanoma detection using delaunay triangulation. / Pennisi, A.; Bloisi, D. D.; Nardi, D.; Giampetruzzi, A. R.; Mondino, C.; Facchiano, A.

Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI. Vol. 2016-January IEEE Computer Society, 2016. p. 791-798 7372213.

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

Pennisi, A, Bloisi, DD, Nardi, D, Giampetruzzi, AR, Mondino, C & Facchiano, A 2016, Melanoma detection using delaunay triangulation. in Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI. vol. 2016-January, 7372213, IEEE Computer Society, pp. 791-798, 27th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2015, Vietri sul Mare, Salerno, Italy, 11/9/15. https://doi.org/10.1109/ICTAI.2015.117
Pennisi A, Bloisi DD, Nardi D, Giampetruzzi AR, Mondino C, Facchiano A. Melanoma detection using delaunay triangulation. In Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI. Vol. 2016-January. IEEE Computer Society. 2016. p. 791-798. 7372213 https://doi.org/10.1109/ICTAI.2015.117
Pennisi, A. ; Bloisi, D. D. ; Nardi, D. ; Giampetruzzi, A. R. ; Mondino, C. ; Facchiano, A. / Melanoma detection using delaunay triangulation. Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI. Vol. 2016-January IEEE Computer Society, 2016. pp. 791-798
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