Preparing digitized cervigrams for colposcopy research and education: determination of optimal resolution and compression parameters.
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.
Jeronimo
Jose
J
Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Bethesda, MD 20892, USA. guibovij@mail.nih.gov
Long
Rodney
R
Neve
Leif
L
Ferris
Daron
D
Noller
Kenneth
K
Spitzer
Mark
M
Mitra
Sunanda
S
Guo
Jiangling
J
Nutter
Brian
B
Castle
Phil
P
Herrero
Rolando
R
Rodriguez
Ana Cecilia
AC
Schiffman
Mark
M
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*