Lossless Compression of Multidimensional Medical Images for Augmented Reality Applications

Medical digital imaging technologies produce daily a huge amount of data (data obtained by magnetic resonance, computed tomography and ultrasound examinations, functional resonance magnetic acquisitions, etc.), which is generally stored in ad-hoc repositories or it is transmitted to other entities,...

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Bibliographic Details
Published inAugmented and Virtual Reality pp. 124 - 136
Main Authors Carpentieri, Bruno, Pizzolante, Raffaele
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing 2014
SeriesLecture Notes in Computer Science
Subjects
Online AccessGet full text
ISBN3319139681
9783319139685
ISSN0302-9743
1611-3349
DOI10.1007/978-3-319-13969-2_10

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Summary:Medical digital imaging technologies produce daily a huge amount of data (data obtained by magnetic resonance, computed tomography and ultrasound examinations, functional resonance magnetic acquisitions, etc.), which is generally stored in ad-hoc repositories or it is transmitted to other entities, such as research centers, hospital structures, etc.. These data need efficient compression, in order to optimize memory space and transmission costs. In this work, we introduce an efficient lossless algorithm that can be used for the compression of volumetric multidimensional medical image sequences. This approach can be also used, in conjunction with Augmented Reality techniques, to save in a database or to transmit on a communication line the outcomes of surgical decisions or medical applications. We experimentally test our approach on a test set of 3-D computed tomography (CT), 3-D magnetic resonance (MR) images, and of 5-D functional Magnetic Resonance Images (fMRI). The achieved results outperform the other state-of-the-art approaches.
ISBN:3319139681
9783319139685
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-13969-2_10