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...

Description complète

Détails bibliographiques
Auteur principal: Saffor, Emhemad Mohamed
Format: Thèse
Langue:anglais
anglais
Publié: 2003
Sujets:
Accès en ligne:http://psasir.upm.edu.my/id/eprint/12160/1/FK_2003_19.pdf
_version_ 1846214924353667072
author Saffor, Emhemad Mohamed
author_facet Saffor, Emhemad Mohamed
author_sort Saffor, Emhemad Mohamed
description 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.
format Thesis
id oai:psasir.upm.edu.my:12160
institution Universiti Putra Malaysia
language English
English
publishDate 2003
record_format eprints
spelling oai:psasir.upm.edu.my:121602024-07-03T03:16:33Z http://psasir.upm.edu.my/id/eprint/12160/ Wavelet-Based Lossy Compression Techniques For Medical Images Saffor, Emhemad Mohamed 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. 2003-05 Thesis NonPeerReviewed text en http://psasir.upm.edu.my/id/eprint/12160/1/FK_2003_19.pdf Saffor, Emhemad Mohamed (2003) Wavelet-Based Lossy Compression Techniques For Medical Images. Doctoral thesis, Universiti Putra Malaysia. X-ray densitometry in medicine Medical imaging equipment industry - Malaysia English
spellingShingle X-ray densitometry in medicine
Medical imaging equipment industry - Malaysia
Saffor, Emhemad Mohamed
Wavelet-Based Lossy Compression Techniques For Medical Images
title Wavelet-Based Lossy Compression Techniques For Medical Images
title_full Wavelet-Based Lossy Compression Techniques For Medical Images
title_fullStr Wavelet-Based Lossy Compression Techniques For Medical Images
title_full_unstemmed Wavelet-Based Lossy Compression Techniques For Medical Images
title_short Wavelet-Based Lossy Compression Techniques For Medical Images
title_sort wavelet based lossy compression techniques for medical images
topic X-ray densitometry in medicine
Medical imaging equipment industry - Malaysia
url http://psasir.upm.edu.my/id/eprint/12160/1/FK_2003_19.pdf
url-record http://psasir.upm.edu.my/id/eprint/12160/
work_keys_str_mv AT safforemhemadmohamed waveletbasedlossycompressiontechniquesformedicalimages