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Published in: International Journal of Computer Assisted Radiology and Surgery 12/2018

01-12-2018 | Original Article

Using the variogram for vector outlier screening: application to feature-based image registration

Authors: Jie Luo, Sarah Frisken, Ines Machado, Miaomiao Zhang, Steve Pieper, Polina Golland, Matthew Toews, Prashin Unadkat, Alireza Sedghi, Haoyin Zhou, Alireza Mehrtash, Frank Preiswerk, Cheng-Chieh Cheng, Alexandra Golby, Masashi Sugiyama, William M. Wells III

Published in: International Journal of Computer Assisted Radiology and Surgery | Issue 12/2018

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Abstract

Purpose

Matching points that are derived from features or landmarks in image data is a key step in some medical imaging applications. Since most robust point matching algorithms claim to be able to deal with outliers, users may place high confidence in the matching result and use it without further examination. However, for tasks such as feature-based registration in image-guided neurosurgery, even a few mismatches, in the form of invalid displacement vectors, could cause serious consequences. As a result, having an effective tool by which operators can manually screen all matches for outliers could substantially benefit the outcome of those applications.

Methods

We introduce a novel variogram-based outlier screening method for vectors. The variogram is a powerful geostatistical tool for characterizing the spatial dependence of stochastic processes. Since the spatial correlation of invalid displacement vectors, which are considered as vector outliers, tends to behave differently than normal displacement vectors, they can be efficiently identified on the variogram.

Results

We validate the proposed method on 9 sets of clinically acquired ultrasound data. In the experiment, potential outliers are flagged on the variogram by one operator and further evaluated by 8 experienced medical imaging researchers. The matching quality of those potential outliers is approximately 1.5 lower, on a scale from 1 (bad) to 5 (good), than valid displacement vectors.

Conclusion

The variogram is a simple yet informative tool. While being used extensively in geostatistical analysis, it has not received enough attention in the medical imaging field. We believe there is a good deal of potential for clinically applying the proposed outlier screening method. By way of this paper, we also expect researchers to find variogram useful in other medical applications that involve motion vectors analyses.
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Metadata
Title
Using the variogram for vector outlier screening: application to feature-based image registration
Authors
Jie Luo
Sarah Frisken
Ines Machado
Miaomiao Zhang
Steve Pieper
Polina Golland
Matthew Toews
Prashin Unadkat
Alireza Sedghi
Haoyin Zhou
Alireza Mehrtash
Frank Preiswerk
Cheng-Chieh Cheng
Alexandra Golby
Masashi Sugiyama
William M. Wells III
Publication date
01-12-2018
Publisher
Springer International Publishing
Published in
International Journal of Computer Assisted Radiology and Surgery / Issue 12/2018
Print ISSN: 1861-6410
Electronic ISSN: 1861-6429
DOI
https://doi.org/10.1007/s11548-018-1840-5

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