A Non-Local Diffusion Saliency Model for Magnetic Resonance Imaging

I. Ramírez, G. Galiano, N. Malpica, E. Schiavi

2017

Abstract

Based on previous work on image classification and recent applications of non-local non-linear diffusion equations, we propose a non-local p-laplacian variational model for saliency detection in digital images. Focusing on the range 0 < p < 1 we also consider the regularized non-convex fluxes generated by the related hyper-laplacian diffusion operators. With the aim of exploring the properties and potential applications of such non-local, non-convex operators the model is applied to Magnetic Resonace Imaging (MRI) for Fluid Attenuated Inversion Recovery image (FLAIR) modality showing promising numerical results. In this work Saliency shall be understood as the relevant, outstanding region in a FLAIR image, which is commonly the brightest part. It corresponds to a tumor and neighborhood edema. Our preliminary experiments show that the proposed model can achieve very accurate results in this modality in terms of all the considered metrics.

Paper Citation

in Harvard Style

Ramírez I., Galiano G., Malpica N. and Schiavi E. (2017). A Non-Local Diffusion Saliency Model for Magnetic Resonance Imaging. In - BIOIMAGING, (BIOSTEC 2017) ISBN , pages 0-0. DOI: 10.5220/0006172100001488

in Bibtex Style

@conference{bioimaging17,
author={I. Ramírez and G. Galiano and N. Malpica and E. Schiavi},
title={A Non-Local Diffusion Saliency Model for Magnetic Resonance Imaging},
booktitle={ - BIOIMAGING, (BIOSTEC 2017)},
year={2017},
pages={},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006172100001488},
isbn={},
}

in EndNote Style

TY - CONF

JO - - BIOIMAGING, (BIOSTEC 2017)
TI - A Non-Local Diffusion Saliency Model for Magnetic Resonance Imaging
SN -
AU - Ramírez I.
AU - Galiano G.
AU - Malpica N.
AU - Schiavi E.
PY - 2017
SP - 0
EP - 0
DO - 10.5220/0006172100001488