Tree structured wavelet transform signature for classification of melanoma

Sachin V. Patwardhan, Atam P. Dhawan, Patricia A. Relue

Research output: Contribution to journalArticlepeer-review

Abstract

The purpose of this work is to evaluate the use of a wavelet transform based tree structure in classifying skin lesion images into melanoma and dysplastic nevus classes based on the spatial/frequency information. The classification is done using the wavelet transform tree structure analysis. Development of the tree structure in the proposed method uses energy ratio thresholds obtained from a statistical analysis of the coefficients in the wavelet domain. The method is used to obtain a tree structure signature of melanoma and dysplastic nevus, which is then used to classify the data set into the two classes. Images are classified by using a semantic comparison of the wavelet transform tree structure signatures. Results show that the proposed method is effective and simple for classification based on spatial/frequency information, which also includes the textural information.

Original languageEnglish (US)
Pages (from-to)1085-1091
Number of pages7
JournalProceedings of SPIE-The International Society for Optical Engineering
Volume4684 II
DOIs
StatePublished - Jan 1 2002

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Applied Mathematics
  • Electrical and Electronic Engineering
  • Computer Science Applications

Keywords

  • Dysplastic Nevus
  • Melanoma
  • Nevoscope
  • Tree Structured Wavelet Transform

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