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Image Compression Based On Region Of Interest For Computerized Tomography Images

The use of computers for handling image data in the healthcare is growing. The amount of data produced by modem image generating techniques, such as Computed Tomography (CT) and Magnetic Resonance (MR), is vast. The amount of data might be a problem from a storage point of view or when the data is s...

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Main Author: Idbeaa, Tarik Faraj Ali
Format: Thesis
Language:English
Published: 2003
Online Access:http://ethesis.upm.edu.my/id/eprint/2854/4/FK_2003_7_F_new.pdf
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id oai:ethesis.upm.edu.my:2854
record_format eprints
spelling oai:ethesis.upm.edu.my:2854 http://ethesis.upm.edu.my/id/eprint/2854/ Image Compression Based On Region Of Interest For Computerized Tomography Images Idbeaa, Tarik Faraj Ali The use of computers for handling image data in the healthcare is growing. The amount of data produced by modem image generating techniques, such as Computed Tomography (CT) and Magnetic Resonance (MR), is vast. The amount of data might be a problem from a storage point of view or when the data is sent over a network. To overcome these problems data compression techniques adapted to these applications are needed. Many classes of images contain some spatial regions which are more important than other regions. Compression methods which are capable of achieving higher reconstruction quality of important parts of the image have been implemented. For medical images, only a small portion of the image might be diagnostically useful, but the cost of wrong interpretation is high. Algorithms which deliver lossless compression within the regions of interest (ROI), and lossy compression elsewhere in the image, might be the key to providing efficient and accurate image coding to the medical community. In this thesis both of compression techniques (lossy and lossless) of medical images using the JPEG algorithm (DCT), will be discussed. 2003-03 Thesis NonPeerReviewed text en http://ethesis.upm.edu.my/id/eprint/2854/4/FK_2003_7_F_new.pdf Idbeaa, Tarik Faraj Ali (2003) Image Compression Based On Region Of Interest For Computerized Tomography Images. Masters thesis, Universiti Putra Malaysia. (FK 2003 7).
institution UPM eTHESES
collection UPM eTHESES
language English
description The use of computers for handling image data in the healthcare is growing. The amount of data produced by modem image generating techniques, such as Computed Tomography (CT) and Magnetic Resonance (MR), is vast. The amount of data might be a problem from a storage point of view or when the data is sent over a network. To overcome these problems data compression techniques adapted to these applications are needed. Many classes of images contain some spatial regions which are more important than other regions. Compression methods which are capable of achieving higher reconstruction quality of important parts of the image have been implemented. For medical images, only a small portion of the image might be diagnostically useful, but the cost of wrong interpretation is high. Algorithms which deliver lossless compression within the regions of interest (ROI), and lossy compression elsewhere in the image, might be the key to providing efficient and accurate image coding to the medical community. In this thesis both of compression techniques (lossy and lossless) of medical images using the JPEG algorithm (DCT), will be discussed.
format Thesis
author Idbeaa, Tarik Faraj Ali
spellingShingle Idbeaa, Tarik Faraj Ali
Image Compression Based On Region Of Interest For Computerized Tomography Images
author_facet Idbeaa, Tarik Faraj Ali
author_sort Idbeaa, Tarik Faraj Ali
title Image Compression Based On Region Of Interest For Computerized Tomography Images
title_short Image Compression Based On Region Of Interest For Computerized Tomography Images
title_full Image Compression Based On Region Of Interest For Computerized Tomography Images
title_fullStr Image Compression Based On Region Of Interest For Computerized Tomography Images
title_full_unstemmed Image Compression Based On Region Of Interest For Computerized Tomography Images
title_sort image compression based on region of interest for computerized tomography images
publishDate 2003
url http://ethesis.upm.edu.my/id/eprint/2854/4/FK_2003_7_F_new.pdf
_version_ 1819310303997853696
score 13.4562235

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