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KLÍMA, O. BAŘINA, D. KLEPÁRNÍK, P. ZEMČÍK, P. CHROMÝ, A. ŠPANĚL, M.
Original Title
Lossy Compression of 3-D Statistical Shape and Intensity Models of Femoral Bones Using JPEG 2000
Type
conference paper
Language
English
Original Abstract
Recent development of computer-assisted medical systems, based on statistical shape analysis, leads to a growing number of emerging shape and appearance models. In this paper, we propose a novel method for a lossy compression of 3-D statistical shape and intensity models exploiting the JPEG 2000 image coding system. We also investigate the influence of the lossy compression on the accuracy of an atlas-based 2D-3D reconstruction, which is one of the common applications of the statistical appearance models. The results revealed the method is highly effective for the intensity information, reaching thousandfold compression ratios without affecting the 2D-3D reconstruction accuracy. The bitrate of shape information can be compressed several times without significant influence on the reconstruction accuracy.
Keywords
medical data processing, statistical shape and intensity model, lossy compression, JPEG 2000, 2D-3D reconstruction
Authors
KLÍMA, O.; BAŘINA, D.; KLEPÁRNÍK, P.; ZEMČÍK, P.; CHROMÝ, A.; ŠPANĚL, M.
Released
30. 8. 2016
Publisher
Elsevier Science
Location
Brno / Lednice
ISBN
2405-8963
Periodical
IFAC-PapersOnLine (ELSEVIER)
Year of study
49
Number
25
State
Kingdom of the Netherlands
Pages from
115
Pages to
120
Pages count
6
BibTex
@inproceedings{BUT132595, author="Ondřej {Klíma} and David {Bařina} and Petr {Klepárník} and Pavel {Zemčík} and Adam {Chromý} and Michal {Španěl}", title="Lossy Compression of 3-D Statistical Shape and Intensity Models of Femoral Bones Using JPEG 2000", booktitle="14th IFAC Conference on Programmable Devices and Embedded Systems PDES 2016 Brno, Czech Republic, 5-7 October 2016", year="2016", journal="IFAC-PapersOnLine (ELSEVIER)", volume="49", number="25", pages="115--120", publisher="Elsevier Science", address="Brno / Lednice", doi="10.1016/j.ifacol.2016.12.020", issn="2405-8963" }