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 language | English (US) |
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Pages (from-to) | 10-15 |
Number of pages | 6 |
Journal | Journal of Lower Genital Tract Disease |
Volume | 10 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2006 |
Keywords
- Cervical neoplasia
- Digital image
- Image compression
- Segmentation
ASJC Scopus subject areas
- Obstetrics and Gynecology