Evaluation of wavelet compression algorithm on computed tomography (CT) images
There is a great need for efficient image compression in medical imaging for archiving and transmission without any significant loss of diagnostic information. Wavelet compression was applied to compress and decompress various sets of computed tomography (CT) images, namely brain, chest, and abdomen...
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2001
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my.upm.eprints.208342016-11-02T03:47:17Z http://psasir.upm.edu.my/id/eprint/20834/ Evaluation of wavelet compression algorithm on computed tomography (CT) images Salfor, Amhamed Ramli, Abdul Rahman Ng, Kwan Hoong Abd Ghani, Abdul Azim Prakash, Veeraraghavan There is a great need for efficient image compression in medical imaging for archiving and transmission without any significant loss of diagnostic information. Wavelet compression was applied to compress and decompress various sets of computed tomography (CT) images, namely brain, chest, and abdomen; the size of each image is 512x512x8 bit. Currently there is no standard set of criteria for the clinical acceptability of compression ratio. Thus we have calculated the mean square error (MSE), signal to noise ratio (SNR), and peak signal to noise ratio (PSNR) as a form of criteria to determine the 'acceptability' of image compression. The Wavelet Compression Engine (standard edition 2.5) was used in this study. The degree of compression is dependent on the anatomical structure and the complexity of the CT images. 2001 Conference or Workshop Item NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/20834/1/ID%2020834.pdf Salfor, Amhamed and Ramli, Abdul Rahman and Ng, Kwan Hoong and Abd Ghani, Abdul Azim and Prakash, Veeraraghavan (2001) Evaluation of wavelet compression algorithm on computed tomography (CT) images. In: Persidangan Kebangsaan Penyelidikan & Pembangunan IPTA 2001, 25-26 Okt. 2001, Universiti Kebangsaan Malaysia, Bangi, Selangor. (pp. 871-877). |
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There is a great need for efficient image compression in medical imaging for archiving and transmission without any significant loss of diagnostic information. Wavelet compression was applied to compress and decompress various sets of computed tomography (CT) images, namely brain, chest, and abdomen; the size of each image is 512x512x8 bit. Currently there is no standard set of criteria for the clinical acceptability of compression ratio. Thus we have calculated the mean square error (MSE), signal to noise ratio (SNR), and peak signal to noise ratio (PSNR) as a form of criteria to determine the 'acceptability' of image compression. The Wavelet Compression Engine (standard edition 2.5) was used in this study. The degree of compression is dependent on the anatomical structure and the complexity of the CT images. |
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Conference or Workshop Item |
author |
Salfor, Amhamed Ramli, Abdul Rahman Ng, Kwan Hoong Abd Ghani, Abdul Azim Prakash, Veeraraghavan |
spellingShingle |
Salfor, Amhamed Ramli, Abdul Rahman Ng, Kwan Hoong Abd Ghani, Abdul Azim Prakash, Veeraraghavan Evaluation of wavelet compression algorithm on computed tomography (CT) images |
author_facet |
Salfor, Amhamed Ramli, Abdul Rahman Ng, Kwan Hoong Abd Ghani, Abdul Azim Prakash, Veeraraghavan |
author_sort |
Salfor, Amhamed |
title |
Evaluation of wavelet compression algorithm on computed
tomography (CT) images |
title_short |
Evaluation of wavelet compression algorithm on computed
tomography (CT) images |
title_full |
Evaluation of wavelet compression algorithm on computed
tomography (CT) images |
title_fullStr |
Evaluation of wavelet compression algorithm on computed
tomography (CT) images |
title_full_unstemmed |
Evaluation of wavelet compression algorithm on computed
tomography (CT) images |
title_sort |
evaluation of wavelet compression algorithm on computed
tomography (ct) images |
publishDate |
2001 |
url |
http://psasir.upm.edu.my/id/eprint/20834/1/ID%2020834.pdf http://psasir.upm.edu.my/id/eprint/20834/ |
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