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Registration and Modeling from Spaced and Misaligned Image Volumes / Adeline, Paiement; Xianghua, Xie

IEEE Transactions on Image Processing, Volume: 25, Issue: 9, Pages: 4379 - 4393

Swansesa University Authors: Adeline, Paiement, Xianghua, Xie

Abstract

We present an integrated registration, segmentation, and shape interpolation framework to model objects from 3D and 4D volumes made up of spaced and misaligned slices having arbitrary relative positions. The framework was validated on artificial data and tested on real MRI and CT scans. The complete...

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Published in: IEEE Transactions on Image Processing
ISSN: 1941-0042
Published: 2016
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa28997
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Abstract: We present an integrated registration, segmentation, and shape interpolation framework to model objects from 3D and 4D volumes made up of spaced and misaligned slices having arbitrary relative positions. The framework was validated on artificial data and tested on real MRI and CT scans. The complete framework performed significantly better than the sequential approach of registration followed by segmentation and shape interpo- lation.
Keywords: Modeling methodologies, registration, segmentation, shape interpolation, level set methods, RBF.
Issue: 9
Start Page: 4379
End Page: 4393