title: Digitized cervical images: problems, solutions, and potential medical impact.
abstract: OBJECTIVE
  To demonstrate compression, illumination enhancement, registration, segmentation, automated classification and steganography using digitized cervical images.
  
  
  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.
authors.affiliation: Gynecologic Cancer Prevention Center, Department of Family Medicine, Medical College of Georgia, Augusta, 30912, USA. dferris@mcg.edu
authors.forename: Daron G
authors.initials: DG
authors.lastname: Ferris
authors.forename: Sunanda
authors.initials: S
authors.lastname: Mitra
authors.forename: Brian
authors.initials: B
authors.lastname: Nutter
mesh_terms: D002584:Cervix Uteri / Q000473:pathology*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D010781:Photography / Q000379:methods*; D015203:Reproducibility of Results; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis*