title: Preparing digitized cervigrams for colposcopy research and education: determination of optimal resolution and compression parameters.
abstract: OBJECTIVE
  Visual assessment of digitized cervigrams through the Internet needs to be optimized. The National Cancer Institute and National Library of Medicine are involved in a large effort to improve colposcopic assessment and, in preparation, are conducting methodologic research.
  
  
  METHODS
  We selected 50 cervigrams with diagnoses ranging from normal to cervical intraepithelial neoplasia 3 or invasive cancer. Those pictures were scanned at 5 resolution levels from 1,550 to 4,000 dots per inch (dpi) and were presented to 4 expert colposcopists to assess image quality. After the ideal resolution level was determined, pictures were compressed at 7 compression ratios from 20:1 to 80:1 to determine the optimal level of compression that permitted full assessment of key visual details.
  
  
  RESULTS
  There were no statistically significant differences between the 3,000 and 4,000 dpi pictures. At 2,000 dpi resolution, only one colposcopist found a slightly statistically significant difference (p = 0.02) compared with the gold standard. There was a clear loss of quality of the pictures at 1,660 dpi. At compression ratio 60:1, 3 of 4 evaluators found statistically significant differences when comparing against the gold standard.
  
  
  CONCLUSIONS
  Our results suggest that 2,000 dpi is the optimal level for digitizing cervigrams, and the optimal compression ratio is 50:1 using a novel wavelet-based technology. At these parameters, pictures have no significant differences with the gold standard.
authors.affiliation: Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Bethesda, MD 20892, USA. guibovij@mail.nih.gov
authors.forename: Jose
authors.initials: J
authors.lastname: Jeronimo
authors.forename: Rodney
authors.initials: R
authors.lastname: Long
authors.forename: Leif
authors.initials: L
authors.lastname: Neve
authors.forename: Daron
authors.initials: D
authors.lastname: Ferris
authors.forename: Kenneth
authors.initials: K
authors.lastname: Noller
authors.forename: Mark
authors.initials: M
authors.lastname: Spitzer
authors.forename: Sunanda
authors.initials: S
authors.lastname: Mitra
authors.forename: Jiangling
authors.initials: J
authors.lastname: Guo
authors.forename: Brian
authors.initials: B
authors.lastname: Nutter
authors.forename: Phil
authors.initials: P
authors.lastname: Castle
authors.forename: Rolando
authors.initials: R
authors.lastname: Herrero
authors.forename: Ana Cecilia
authors.initials: AC
authors.lastname: Rodriguez
authors.forename: Mark
authors.initials: M
authors.lastname: Schiffman
mesh_terms: D035843:Biomedical Research; D002584:Cervix Uteri / Q000473:pathology*; D003127:Colposcopy / Q000379:methods*; D005260:Female; D006176:Gynecology / Q000193:education*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis*