Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 884

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Comparison and Evaluation of Retrospective Intermodality Brain Image Registration Techniques

Open access
West, Jay, Fitzpatrick, J. Michael, Wang, Matthew Y., Dawant, Benoit M., Maurer, Calvin R., Kessler, Robert M., Maciunas, Robert J., Barillot, Christian, Lemoine, Didier, Collignon, André, Maes, Frederik, Suetens, Paul, Vandermeulen, Dirk, van den Elsen, Petra A., Napel, Sandy, Sumanaweera, Thilaka S., Harkness, Beth, Hemler, Paul F., Hill, Derek L. G., Hawkes, David J., Studholme, Colin, Maintz, J. B. Antoine, Viergever, Max A., Malandain, Gregoire, Pennec, Xavier, Noz, Marilyn E., Maguire, Gerald Q., Pollack, Michael, Pelizzari, Charles A., Robb, Richard A., Hanson, Dennis, Woods, Roger P.·1997·Journal of Computer Assisted Tomography

Abstract

PURPOSE: The primary objective of this study is to perform a blinded evaluation of a group of retrospective image registration techniques using as a gold standard a prospective, marker-based registration method. To ensure blindedness, all retrospective registrations were performed by participants who had no knowledge of the gold standard results until after their results had been submitted. A secondary goal of the project is to evaluate the importance of correcting geometrical distortion in MR images by comparing the retrospective registration error in the rectified images, i.e., those that have had the distortion correction applied, with that of the same images before rectification. METHOD: Image volumes of three modalities (CT, MR, and PET) were obtained from patients undergoing neurosurgery at Vanderbilt University Medical Center on whom bone-implanted fiducial markers were mounted. These volumes had all traces of the markers removed and were provided via the Internet to project collaborators outside Vanderbilt, who then performed retrospective registrations on the volumes, calculating transformations from CT to MR and/ or from PET to MR. These investigators communicated their transformations again via the Internet to Vanderbilt, where the accuracy of each registration was evaluated. In this evaluation, the accuracy is measured at multiple volumes of interest (VOIs), i.e., areas in the brain that would commonly be areas of neurological interest. A VOI is defined in the MR image and its centroid c is determined. Then, the prospective registration is used to obtain the corresponding point c' in CT or PET. To this point, the retrospective registration is then applied, producing c" in MR. Statistics are gathered on the target registration error (TRE), which is the distance between the original point c and its corresponding point c". RESULTS: This article presents statistics on the TRE calculated for each registration technique in this study and provides a brief description of each technique and an estimate of both preparation and execution time needed to perform the registration. CONCLUSION: Our results indicate that retrospective techniques have the potential to produce satisfactory results much of the time, but that visual inspection is necessary to guard against large errors.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1097/00004728-199707000-00007

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 884

Metadata

Authors
West, J., Fitzpatrick, J. M., Wang, M. Y., Dawant, B. M., Maurer, C. R., Kessler, R. M., Maciunas, R. J., Barillot, C., Lemoine, D., Collignon, A., Maes, F., Suetens, P., Vandermeulen, D., van den Elsen, P. A., Napel, S., Sumanaweera, T. S., Harkness, B., Hemler, P. F., Hill, D. L. G., Hawkes, D. J., Studholme, C., Maintz, J. B. A., Viergever, M. A., Malandain, G., Pennec, X., Noz, M. E., Maguire, G. Q., Pollack, M., Pelizzari, C. A., Robb, R. A., Hanson, D., & Woods, R. P.
Venue
Journal of Computer Assisted Tomography
Published
1997-07
Volume
21
Issue
4
Pages
554-568
ISSN
0363-8715 (ISSN-L)
OpenAlex
W2134165173
Cited by
884
References
1
FWCI
49.02
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Comparison and Evaluation of Retrospective Intermodality Brain Image Registration Techniques. https://app.cochat.ai/papers/10.1097/00004728-199707000-00007
The paper
West, J., Fitzpatrick, J. M., Wang, M. Y., Dawant, B. M., Maurer, C. R., Kessler, R. M., Maciunas, R. J., Barillot, C., Lemoine, D., Collignon, A., Maes, F., Suetens, P., Vandermeulen, D., van den Elsen, P. A., Napel, S., Sumanaweera, T. S., Harkness, B., Hemler, P. F., Hill, D. L. G., . . . Woods, R. P. (1997). Comparison and Evaluation of Retrospective Intermodality Brain Image Registration Techniques. Journal of Computer Assisted Tomography. https://doi.org/10.1097/00004728-199707000-00007

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.