Geometric steerable medial maps

To provide more intuitive and easily interpretable representations of complex shapes/organs, medial manifolds should reach a compromise between simplicity in geometry and capability of restoring the anatomy/shape of the organ/volume. Existing morphological methods show excellent results when applied...

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Veröffentlicht in:Machine vision and applications 2013-08, Vol.24 (6), p.1255-1266
Hauptverfasser: Vera, Sergio, Gil, Debora, Borràs, Agnés, Linguraru, Marius George, González Ballester, Miguel Angel
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container_issue 6
container_start_page 1255
container_title Machine vision and applications
container_volume 24
creator Vera, Sergio
Gil, Debora
Borràs, Agnés
Linguraru, Marius George
González Ballester, Miguel Angel
description To provide more intuitive and easily interpretable representations of complex shapes/organs, medial manifolds should reach a compromise between simplicity in geometry and capability of restoring the anatomy/shape of the organ/volume. Existing morphological methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds from a theoretical and a practical point of view. First, we introduce a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. Second, we present a validation protocol for assessing the suitability of medial surfaces for anatomical representation in medical applications. We evaluate quantitatively the performance of our method with respect to existing approaches and show its higher performance for medical imaging applications in terms of medial simplicity and capability of reconstructing the anatomical volume.
doi_str_mv 10.1007/s00138-013-0490-4
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source SpringerNature Journals
subjects Anatomy
Biological and medical sciences
Communications Engineering
Computational efficiency
Computer Science
Image Processing and Computer Vision
Investigative techniques, diagnostic techniques (general aspects)
Machine vision
Manifolds
Manifolds (mathematics)
Medical imaging
Medical sciences
Networks
Operators (mathematics)
Organs
Original Paper
Pattern Recognition
Renovating
Representations
Vision systems
title Geometric steerable medial maps
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