Publication
Title
The reconstructed residual error : a novel segmentation evaluation measure for reconstructed images in tomography
Author
Abstract
In this paper, we present the reconstructed residual error, which evaluates the quality of a given segmentation of a reconstructed image in tomography. This novel evaluation method, which is independent of the methods that were used to reconstruct and segment the image, is applicable to segmentations that are based on the density of the scanned object. It provides a spatial map of the errors in the segmented image, based on the projection data. The reconstructed residual error is a reconstruction of the difference between the recorded data and the forward projection of that segmented image. The properties and applications of the algorithm are verified experimentally through simulations and experimental micro-CT data. The experiments show that the reconstructed residual error is close to the true error, that it can improve gray level estimates, and that it can help discriminating between different segmentations. (C) 2014 Elsevier Inc. All rights reserved.
Language
English
Source (journal)
Computer vision and image understanding. - -
Publication
2014
ISSN
1077-3142
DOI
10.1016/J.CVIU.2014.05.007
Volume/pages
126 (2014) , p. 28-37
ISI
000339646800003
Full text (Publisher's DOI)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Project info
Quantitative tomographic segmentation of magnetic resonance images
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 08.09.2014
Last edited 09.10.2023
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