Minimize the Percentage of Noise in Biomedical Images Using Neural Networks
The overall goal of the research is to improve the quality of biomedical image for telemedicine with minimum percentages of noise in the retrieved image and to take less computation time. The novelty of this technique lies in the implementation of spectral coding for biomedical images using neural n...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
|
| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/757146 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849307665150246912 |
|---|---|
| author | Abdul Khader Jilani Saudagar |
| author_facet | Abdul Khader Jilani Saudagar |
| author_sort | Abdul Khader Jilani Saudagar |
| collection | DOAJ |
| description | The overall goal of the research is to improve the quality of biomedical image for telemedicine with minimum percentages of noise in the retrieved image and to take less computation time. The novelty of this technique lies in the implementation of spectral coding for biomedical images using neural networks in order to accomplish the above objectives. This work is in continuity of an ongoing research project aimed at developing a system for efficient image compression approach for telemedicine in Saudi Arabia. We compare the efficiency of this technique against existing image compression techniques, namely, JPEG2000, in terms of compression ratio, peak signal to noise ratio (PSNR), and computation time. To our knowledge, the research is the primary in providing a comparative study with other techniques used in the compression of biomedical images. This work explores and tests biomedical images such as X-rays, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). |
| format | Article |
| id | doaj-art-2171db561a814d49baafaf89bf40696c |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-2171db561a814d49baafaf89bf40696c2025-08-20T03:54:42ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/757146757146Minimize the Percentage of Noise in Biomedical Images Using Neural NetworksAbdul Khader Jilani Saudagar0Department of Information Systems, College of Computers and Information Sciences, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), P.O. Box 5701, Riyadh 11432, Saudi ArabiaThe overall goal of the research is to improve the quality of biomedical image for telemedicine with minimum percentages of noise in the retrieved image and to take less computation time. The novelty of this technique lies in the implementation of spectral coding for biomedical images using neural networks in order to accomplish the above objectives. This work is in continuity of an ongoing research project aimed at developing a system for efficient image compression approach for telemedicine in Saudi Arabia. We compare the efficiency of this technique against existing image compression techniques, namely, JPEG2000, in terms of compression ratio, peak signal to noise ratio (PSNR), and computation time. To our knowledge, the research is the primary in providing a comparative study with other techniques used in the compression of biomedical images. This work explores and tests biomedical images such as X-rays, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET).http://dx.doi.org/10.1155/2014/757146 |
| spellingShingle | Abdul Khader Jilani Saudagar Minimize the Percentage of Noise in Biomedical Images Using Neural Networks The Scientific World Journal |
| title | Minimize the Percentage of Noise in Biomedical Images Using Neural Networks |
| title_full | Minimize the Percentage of Noise in Biomedical Images Using Neural Networks |
| title_fullStr | Minimize the Percentage of Noise in Biomedical Images Using Neural Networks |
| title_full_unstemmed | Minimize the Percentage of Noise in Biomedical Images Using Neural Networks |
| title_short | Minimize the Percentage of Noise in Biomedical Images Using Neural Networks |
| title_sort | minimize the percentage of noise in biomedical images using neural networks |
| url | http://dx.doi.org/10.1155/2014/757146 |
| work_keys_str_mv | AT abdulkhaderjilanisaudagar minimizethepercentageofnoiseinbiomedicalimagesusingneuralnetworks |