Wavelet-Based Lossy Compression Techniques For Medical Images
Medical imaging is a powerful and useful tool for radiologists and consultants, allowing them to improve and facilitate their diagnosis. Worldwide, X-ray images represent 60% of the total amount of radiological images, the remaining consists of more newly developed image modalities such as Comput...
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| 主要作者: | |
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| 格式: | Thesis |
| 語言: | English English |
| 出版: |
2003
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| 主題: | |
| 在線閱讀: | http://psasir.upm.edu.my/id/eprint/12160/1/FK_2003_19.pdf |
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| 總結: | Medical imaging is a powerful and useful tool for radiologists and consultants, allowing
them to improve and facilitate their diagnosis. Worldwide, X-ray images represent 60%
of the total amount of radiological images, the remaining consists of more newly
developed image modalities such as Computed Tomography (CT), Magnetic Resonance
Imaging (MRI), Ultrasound (US), Positron Emission Tomography (PET), Single Photon
Emission Computerized Tomography (SPECT), Nuclear Medicine (NM), and Digital
Subtraction Angiography (DSA).
Image communication systems for medical images have bandwidth and image size
constraints that result in time-consuming transmission of uncompressed raw image data.
Thus image compression is a key factor to improve transmission speed and storage, but
it risks losing relevant medical information. The radiology standard Digital Imaging and Communications in Medicine (DICOM3) provides rules for compression using lossless
Joint Photographic Expert Group (JPEG) methods. However, at the moment there are no
rules for acceptance of lossy compression in medical imaging and it is an extremely
subjective decision. Acceptable levels of compression should never compromise
diagnostic information. Wavelet technology has emerged as a promising compression
tool to achieve a high compression ratio while maintaining an acceptable fidelity of
image quality. |
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