loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: A. Nikonorov 1 ; A. Kolsanov 2 ; M. Petrov 1 ; Y. Yuzifovich 3 ; E. Prilepin 4 and K. Bychenkov 4

Affiliations: 1 Samara State Aerospace University and Russian Academy of Science, Russian Federation ; 2 Samara State Medical University, Russian Federation ; 3 Samara State Medical University, Russian Federation ; 4 SmedX LLC, Russian Federation

Keyword(s): Contrast to Noise Ratio; Total Variance De-noising; Liver; Vessels Segmentation; CUDA; GPGPU; Xeon Phi, Proximal Algorithms; Fast Marching; Geodesic Active Contours

Related Ontology Subjects/Areas/Topics: Biomedical Applications ; Image and Video Processing, Compression and Segmentation ; Multimedia ; Multimedia Signal Processing ; Multimedia Systems and Applications ; Telecommunications

Abstract: We analyse CT image denoising when applied to vessel segmentation. Proposed semi-global quality metric based on the contrast-to-noise ratio allowed us to estimate initial image quality and efficiency of denoising procedures without prior knowledge about a noise-free image. We show that the total variance filtering in L1 metric provides the best denoising when compared to other well-known denoising procedures such as non-local means denoising or anisotropic diffusion. Computational complexity of this denoising algorithm is addressed by comparing its implementation for Intel MIC and for NVIDIA CUDA HPC systems.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.208.135.174

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Nikonorov, A.; Kolsanov, A.; Petrov, M.; Yuzifovich, Y.; Prilepin, E. and Bychenkov, K. (2015). Contrast-to-Noise based Metric of Denoising Algorithms for Liver Vein Segmentation. In Proceedings of the 12th International Conference on Signal Processing and Multimedia Applications (ICETE 2015) - SIGMAP; ISBN 978-989-758-118-2, SciTePress, pages 59-67. DOI: 10.5220/0005542400590067

@conference{sigmap15,
author={A. Nikonorov. and A. Kolsanov. and M. Petrov. and Y. Yuzifovich. and E. Prilepin. and K. Bychenkov.},
title={Contrast-to-Noise based Metric of Denoising Algorithms for Liver Vein Segmentation},
booktitle={Proceedings of the 12th International Conference on Signal Processing and Multimedia Applications (ICETE 2015) - SIGMAP},
year={2015},
pages={59-67},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005542400590067},
isbn={978-989-758-118-2},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Signal Processing and Multimedia Applications (ICETE 2015) - SIGMAP
TI - Contrast-to-Noise based Metric of Denoising Algorithms for Liver Vein Segmentation
SN - 978-989-758-118-2
AU - Nikonorov, A.
AU - Kolsanov, A.
AU - Petrov, M.
AU - Yuzifovich, Y.
AU - Prilepin, E.
AU - Bychenkov, K.
PY - 2015
SP - 59
EP - 67
DO - 10.5220/0005542400590067
PB - SciTePress