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Riemannian Median and Its Applications for Orientation Distribution Function Computing

Jian Cheng 1, 2, * Aurobrata Ghosh 1 Tianzi Jiang 2 Rachid Deriche 1 
* Corresponding author
1 ATHENA - Computational Imaging of the Central Nervous System
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : The geometric median is a classic robust estimator of centrality for data in Euclidean spaces, and it has been generalized in analytical manifold in [1]. Recently, an intrinsic Riemannian framework for Orientation Distribution Function (ODF) was proposed for the calculation in ODF field [2]. In this work, we prove the unique existence of the Riemannian median in ODF space. Then we explore its two potential applications, median filtering and atlas estimation.
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Contributor : Jian Cheng Connect in order to contact the contributor
Submitted on : Friday, July 2, 2010 - 7:02:20 PM
Last modification on : Saturday, June 25, 2022 - 11:04:34 PM
Long-term archiving on: : Monday, October 4, 2010 - 12:14:37 PM


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  • HAL Id : inria-00497246, version 1
  • PRODINRA : 247460



Jian Cheng, Aurobrata Ghosh, Tianzi Jiang, Rachid Deriche. Riemannian Median and Its Applications for Orientation Distribution Function Computing. 18th Scientific Meeting and Exhibition of the (ISMRM), 2010, Stockholm, Sweden. ⟨inria-00497246⟩



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