Wavelet-based medical image compression

dc.contributor.author	Κοφίδης, Ελευθέριος	el
dc.contributor.author	Κολοκοτρώνης, Νικόλας	el
dc.contributor.author	Βασιλαράκου, Α.	el
dc.contributor.author	Θεοδωρίδης, Σέργιος	el
dc.contributor.author	Κάβουρας, Διονύσης Α.	el
dc.date.accessioned	2015-04-29T08:41:43Z
dc.date.available	2015-04-29T08:41:43Z
dc.date.issued	2015-04-29
dc.identifier.uri	http://hdl.handle.net/11400/9231
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://www.sciencedirect.com/science/article/pii/S0167739X98000661	en
dc.subject	Medical imaging
dc.subject	Image compression
dc.subject	Ιατρική απεικόνιση
dc.subject	Συμπίεση εικόνας
dc.title	Wavelet-based medical image compression	en
heal.type	journalArticle
heal.classification	Medicine
heal.classification	Biomedical engineering
heal.classification	Ιατρική
heal.classification	Βιοϊατρική τεχνολογία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85014237
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Βιοϊατρική τεχνολογία
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh93007919
heal.identifier.secondary	doi:10.1016/S0167-739X(98)00066-1
heal.language	en
heal.access	campus
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε	el
heal.publicationDate	1999
heal.bibliographicCitation	Kofidis, E., Kolokotronis, N., Vassilarakou, A., Theodoridis, S. and Cavouras, D. (March 1999). Wavelet-based medical image compression. Future Generation Computer Systems. 15(2). pp. 223-243. Elsevier Science B.V: 1999. Available from: http://www.sciencedirect.com/science/article/pii/S0167739X98000661 [Accessed 21/04/2000]	en
heal.abstract	In view of the increasingly important role played by digital medical imaging in modern health care and the consequent blow up in the amount of image data that have to be economically stored and/or transmitted, the need for the development of image compression systems that combine high compression performance and preservation of critical information is ever growing. A powerful compression scheme that is based on the state-of-the-art in wavelet-based compression is presented in this paper. Compression is achieved via efficient encoding of wavelet zerotrees (with the embedded zerotree wavelet (EZW) algorithm) and subsequent entropy coding. The performance of the basic version of EZW is improved upon by a simple, yet effective, way of a more accurate estimation of the centroids of the quantization intervals, at a negligible cost in side information. Regarding the entropy coding stage, a novel RLE-based coder is proposed that proves to be much simpler and faster yet only slightly worse than context-dependent adaptive arithmetic coding. A useful and flexible compromise between the need for high compression and the requirement for preservation of selected regions of interest is provided through two intelligent, yet simple, ways of achieving the so-called selective compression. The use of the lifting scheme in achieving compression that is guaranteed to be lossless in the presence of numerical inaccuracies is being investigated with interesting preliminary results. Experimental results are presented that verify the superiority of our scheme over conventional block transform coding techniques (JPEG) with respect to both objective and subjective criteria. The high potential of our scheme for progressive transmission, where the regions of interest are given the highest priority, is also demonstrated.	en
heal.publisher	Elsevier Science B.V	en
heal.journalName	Future Generation Computer Systems	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true