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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Youssif, A.A.A. Chowdhury, M.U. Ray, S. |
| Copyright Year | 2005 |
| Description | Author affiliation: Helwan University (Youssif, A.A.A.) |
| Abstract | This paper is a result of a fruitful cooperation between the computer science and the dental diagnosis experiences. The study presents a new approach of applying computer algorithms to radiographic images of dental implantation used for bone regeneration. We focus here only on the contribution of the computer assistance to the clinical research as the periodontal therapy is beyond the scope of this paper. The proposed system is based on a pattern recognition approach, directed to recognize density changes in the intra-bony affected areas of patients. It comprises different modules with new algorithms specially designed to treat the patients radiographic images more accurately. The system includes digitizing, detecting the complicated region of interest (ROI), defining reference area to correct any projection discrepancy of the follow up images, and finally to extract the distinguishing features of the ROI as a basis for determining the rate of new bone density accumulation. This study is applied to two typical dental cases for a patient who received two different operations. The results are very encouraging and more accurate than traditional techniques reported before. |
| Starting Page | 43 |
| Ending Page | 43 |
| File Size | 444513 |
| Page Count | 1 |
| File Format | |
| ISBN | 0769524672 |
| DOI | 10.1109/DICTA.2005.23 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2005-12-06 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | IEEE/CSP |
| Subject Keyword | radiographic images Medical treatment Standardization computer aided analysis Dentistry Pattern recognition X-ray imaging Image analysis Implants region of interest Bones Diagnostic radiography Computer aided analysis pattern recognition |
| Content Type | Text |
| Resource Type | Article |
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