Digitized cervical images: problems, solutions, and potential medical impact.
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.
Ferris
Daron G
DG
Gynecologic Cancer Prevention Center, Department of Family Medicine, Medical College of Georgia, Augusta, 30912, USA. dferris@mcg.edu
Mitra
Sunanda
S
Nutter
Brian
B
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*