Graph-Based Compensated Wavelet Lifting for 3-D+t Medical CT Data
Lanz D, Kaup A (2016)
Publication Language: English
Publication Type: Conference contribution
Publication year: 2016
Event location: Nuremberg
ISBN: 978-1-5090-5966-9
Abstract
An efficient scalable data representation is an important task especially in the medical area, e.g. for volumes from Computed Tomography (CT) or Magnetic Resonance Tomography (MRT), when a downscaled version of the original signal is needed. Image and video coders based on wavelet transforms provide an adequate way to naturally achieve scalability. This paper presents a new approach for improving the visual quality of the lowpass band by using a novel graph-based method for motion compensation, which is an important step considering data compression. We compare different kinds of neighborhoods for graph construction and demonstrate that a higher amount of referenced nodes increases the quality of the lowpass band while the mean energy of the highpass band decreases. We show that for cardiac CT data the proposed method outperforms a traditional mesh-based approach of motion compensation by approximately 11 dB in terms of PSNR of the lowpass band. Also the mean energy of the highpass band decreases by around 30%.
Authors with CRIS profile
Daniela Wokusch
Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS)
Andre Kaup
Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS)
How to cite
APA:
Lanz, D., & Kaup, A. (2016). Graph-Based Compensated Wavelet Lifting for 3-D+t Medical CT Data. In Proceedings of the Picture Coding Symposium. Nuremberg, DE.
MLA:
Lanz, Daniela, and André Kaup. "Graph-Based Compensated Wavelet Lifting for 3-D+t Medical CT Data." Proceedings of the Picture Coding Symposium, Nuremberg 2016.
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