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Scientific paper - Original scientific paper
Application of Novel Lossless Compression of Medical Images Using Prediction and Contextual Error Modeling
Collegium antropologicum, 31 (2007), 4; 1143-1150. urn:nbn:hr:239:775382
Knezović, Josip; Kovač, Mario; Klapan, Ivica; Mlinarić, Hrvoje; Vranješ, Željko; Lukinović, Juraj; Rakić, Mladen

Institutional repository: Repository UHC Osijek

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Knezović, J., Kovač, M., Klapan, I., Mlinarić, H., Vranješ, Ž., Lukinović, J. & Rakić, M. (2007). Application of Novel Lossless Compression of Medical Images Using Prediction and Contextual Error Modeling. Collegium antropologicum, 31. (4), 1143-1150. Retrieved from https://urn.nsk.hr/urn:nbn:hr:239:775382

Knezović, Josip, et al. "Application of Novel Lossless Compression of Medical Images Using Prediction and Contextual Error Modeling." Collegium antropologicum, vol. 31, no. 4, 2007, pp. 1143-1150. https://urn.nsk.hr/urn:nbn:hr:239:775382

Knezović, Josip, Mario Kovač, Ivica Klapan, Hrvoje Mlinarić, Željko Vranješ, Juraj Lukinović and Mladen Rakić. "Application of Novel Lossless Compression of Medical Images Using Prediction and Contextual Error Modeling." Collegium antropologicum 31, no. 4 (2007): 1143-1150. https://urn.nsk.hr/urn:nbn:hr:239:775382

Knezović, J., et al. (2007) 'Application of Novel Lossless Compression of Medical Images Using Prediction and Contextual Error Modeling', Collegium antropologicum, 31(4), pp. 1143-1150. Available at: https://urn.nsk.hr/urn:nbn:hr:239:775382 (Accessed 23 November 2024)

Knezović J, Kovač M, Klapan I, Mlinarić H, Vranješ Ž, Lukinović J, and sur.. Application of Novel Lossless Compression of Medical Images Using Prediction and Contextual Error Modeling. Collegium antropologicum [Internet]. 2007 [cited 2024 November 23];31(4):1143-1150. Available at: https://urn.nsk.hr/urn:nbn:hr:239:775382

J. Knezović, et al., "Application of Novel Lossless Compression of Medical Images Using Prediction and Contextual Error Modeling", Collegium antropologicum, vol. 31, no. 4, pp. 1143-1150, 2007. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:239:775382. [Accessed: 23 November 2024]

Metadata
Title (english)Application of Novel Lossless Compression of Medical Images Using Prediction and Contextual Error Modeling
Title (croatian)Aplikacija nove metode kompresije medicinskih snimaka bez gubitaka, korištenjem predikcije i kontekstualnog modeliranja
AuthorJosip Knezović
MBZ: 248314
AuthorMario Kovač
MBZ: 165775
AuthorIvica Klapan
MBZ: 137820
AuthorHrvoje Mlinarić
MBZ: 218311
AuthorŽeljko Vranješ
MBZ: 201762
AuthorJuraj Lukinović
AuthorMladen Rakić
MBZ: 170962
Author's institution(Clinical hospital center Osijek)
Author's institutionUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Scientific / art field,
discipline and subdiscipline		BIOMEDICINE AND HEALTHCARE
Clinical Medical Sciences
Anesthesiology and Reanimatology
Scientific / art field,
discipline and subdiscipline		BIOMEDICINE AND HEALTHCARE
Clinical Medical Sciences
Surgery
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract (english)
Conduction of tele-3D-computer assisted operations as well as other telemedicine procedures often requires highest possible quality of transmitted medical images and video. Unfortunately, those data types are always associated with high telecommunication and storage costs that sometimes prevent more frequent usage of such procedures. We present a novel algorithm for lossless compression of medical images that is extremely helpful in reducing the telecommunication and storage costs. The algorithm models the image properties around the current, unknown pixel and adjusts itself to the local image region. The main contribution of this work is the enhancement of the well known approach of predictor blends through highly adaptive determination of blending context on a pixel-by-pixel basis using classification technique. We show that this approach is well suited for medical image data compression. Results obtained with the proposed compression method on medical images are very encouraging, beating several well known lossless compression methods. The predictor proposed can also be used in other image processing applications such as segmentation and extraction of image regions.
Abstract (croatian)
Provođenje tele-3D računalom potpomognutih zahvata kao i druge telemedicinske procedure često zahtjevaju največu moguću kvalitetu medicinskih snimki i videa. Nažalost, takve vrste podataka su uvijek vezane uz visoke telekomunikacijske troškove i troškove pohrane, koji ponekad sprječavaju širu uporabu ovih procedura. Ovdje predstavljamo novi algoritam za kompresiju bez gubitaka medicinskih snimki, koji je od velike pomoći u smanjenju troškova. Glavni doprinos ovog rada je poboljšanje već poznatih modela. Pokazali smo da je ovaj pristup primjeren za kompresiju medicinskih slika. Rezultati dobiveni predloženim načinom kompresije su vrlo ohrabruju}i i pobijaju nekoliko dobro poznatih načina kompresije bez gubitaka. Predloženi prediktor se također može koristiti i u drugim aplikacijama za obradu slika, kao što je segmentiranje i ekstrakcija slikovnih područja.
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Journal titleCollegium antropologicum
Numberingvol. 31, no. 4, pp. 1143-1150
p-ISSN0350-6134
URN:NBNurn:nbn:hr:239:775382
Publication2007
Document URLhttps://hrcak.srce.hr/26983
Type of resourceText
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2020-04-02 09:15:03