Digitized cervical images: Problems, solutions, and potential medical impact

Daron G. Ferris, Sunanda Mitra, Brian Nutter

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

Abstract

OBJECTIVE: To demonstrate compression, illumination enhancement, registration, segmentation, automated classification and steganography using digitized cervical images. MATERIALS AND METHODS: The Hybrid Multi-Scale Vector Quantization algorithm developed at Texas Technological University and other automated systems were used to improve digitized cervical images. RESULTS: We demonstrated high levels of image compression, illumination enhancement, registration, automated segmentation and classification and steganography of digitized cervical images. CONCLUSIONS: Digitized cervical images can be altered to facilitate research of cervical neoplasia.

Original languageEnglish
Pages (from-to)10-15
Number of pages6
JournalJournal of Lower Genital Tract Disease
Volume10
Issue number1
DOIs
StatePublished - Jan 2006

Keywords

  • Cervical neoplasia
  • Digital image
  • Image compression
  • Segmentation

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