Study of Melanocytic Nevi using image processing

Sameena Pathan, P. C. Siddalingaswamy, Gopalakrishna Prabhu

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

1 Citation (Scopus)

Abstract

Melanocytic nevi are benign pigmented skin lesions associated with increased risk of transforming into malignant lesions. Most of the malignant lesions are misclassified as Clark Nevi based on the dermoscopic criteria. Histopathological analysis forms a gold standard. However, this leads to unnecessary biopsies of benign lesions. Thus the identification of benign lesion from malignant lesions plays a prominent role in diagnosis of melanoma. Although significant progress has been made in developing automated diagnostic tools, there exists a need for developing reliable non-invasive diagnostic tools. This can be achieved by incorporating the detection of dermoscopic features based on their histopathological relevance. This study uniquely provides the histopathological correlations of dermoscopic features to facilitate reliable non-invasive diagnosis. The relevance of the dermoscopic features are provided. It is inferred that shape, color and dermoscopic features such as blue-white veil and pigment network would contribute significantly to the field of melanoma diagnosis.

Original languageEnglish
Title of host publicationRTEICT 2017 - 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages368-372
Number of pages5
Volume2018-January
ISBN (Electronic)9781509037049
DOIs
Publication statusPublished - 12-01-2018
Event2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2017 - Bangalore, India
Duration: 19-05-201720-05-2017

Conference

Conference2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2017
CountryIndia
CityBangalore
Period19-05-1720-05-17

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Media Technology
  • Control and Optimization
  • Instrumentation
  • Transportation
  • Communication

Cite this

Pathan, S., Siddalingaswamy, P. C., & Prabhu, G. (2018). Study of Melanocytic Nevi using image processing. In RTEICT 2017 - 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, Proceedings (Vol. 2018-January, pp. 368-372). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RTEICT.2017.8256618