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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| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2001
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| Online Access: | http://psasir.upm.edu.my/id/eprint/20834/1/ID%2020834.pdf http://psasir.upm.edu.my/id/eprint/20834/ |
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| Institution: | Universiti Putra Malaysia |
| Language: | English |
| Summary: | 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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