Abstract
For multimodality image registration, mutual information has become the similarity measure of choice, due to its flexibility, theoretical elegance and general robustness. An essential element in any image registration algorithm is interpolation, which is needed to evaluate voxel intensities at non-grid positions. Interpolation has been a topic of considerable study and the performance of many interpolators has been characterized. Nevertheless, interpolation has some unexpected influence on registration accuracy, causing artifactual fluctuations in the estimated value of mutual information. These "interpolation artifacts" are not reduced by using interpolators with higher accuracy. This surprising finding warranted further investigation into the role of interpolation methods in multimodality image registration. This chapter reviews several commonly used interpolation methods, the application of such methods and the associated problems. A theoretical analysis of the underlying cause of these interpolation artifacts is described. Finally, several strategies are outlined to reduce these artifacts and to improve registration robustness. Such strategies are also applicable to related similarity measures, including normalized mutual information, joint entropy, and Hill’s third moment.
| Original language | English |
|---|---|
| Title of host publication | Medical Imaging Systems Technology: Analysis and Computational Methods |
| Publisher | World Scientific Publishing Co. |
| Pages | 255-295 |
| Number of pages | 41 |
| ISBN (Electronic) | 9789812705785 |
| ISBN (Print) | 9812563644, 9789812569936 |
| DOIs | |
| Publication status | Published - 1 Jan 2005 |
| Externally published | Yes |
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Keywords
- Artifact pattern
- Artifact reduction
- Image registration
- Interpolation artifacts
- Multi-modality
- Mutual information
ASJC Scopus subject areas
- Medicine(all)
Cite this
Interpolation techniques in multimodality image registration and their application. / Tsao, Jeffrey; Ji, Jim; Liang, Zhi Pei.
Medical Imaging Systems Technology: Analysis and Computational Methods. World Scientific Publishing Co., 2005. p. 255-295.Research output: Chapter in Book/Report/Conference proceeding › Chapter
}
TY - CHAP
T1 - Interpolation techniques in multimodality image registration and their application
AU - Tsao, Jeffrey
AU - Ji, Jim
AU - Liang, Zhi Pei
PY - 2005/1/1
Y1 - 2005/1/1
N2 - For multimodality image registration, mutual information has become the similarity measure of choice, due to its flexibility, theoretical elegance and general robustness. An essential element in any image registration algorithm is interpolation, which is needed to evaluate voxel intensities at non-grid positions. Interpolation has been a topic of considerable study and the performance of many interpolators has been characterized. Nevertheless, interpolation has some unexpected influence on registration accuracy, causing artifactual fluctuations in the estimated value of mutual information. These "interpolation artifacts" are not reduced by using interpolators with higher accuracy. This surprising finding warranted further investigation into the role of interpolation methods in multimodality image registration. This chapter reviews several commonly used interpolation methods, the application of such methods and the associated problems. A theoretical analysis of the underlying cause of these interpolation artifacts is described. Finally, several strategies are outlined to reduce these artifacts and to improve registration robustness. Such strategies are also applicable to related similarity measures, including normalized mutual information, joint entropy, and Hill’s third moment.
AB - For multimodality image registration, mutual information has become the similarity measure of choice, due to its flexibility, theoretical elegance and general robustness. An essential element in any image registration algorithm is interpolation, which is needed to evaluate voxel intensities at non-grid positions. Interpolation has been a topic of considerable study and the performance of many interpolators has been characterized. Nevertheless, interpolation has some unexpected influence on registration accuracy, causing artifactual fluctuations in the estimated value of mutual information. These "interpolation artifacts" are not reduced by using interpolators with higher accuracy. This surprising finding warranted further investigation into the role of interpolation methods in multimodality image registration. This chapter reviews several commonly used interpolation methods, the application of such methods and the associated problems. A theoretical analysis of the underlying cause of these interpolation artifacts is described. Finally, several strategies are outlined to reduce these artifacts and to improve registration robustness. Such strategies are also applicable to related similarity measures, including normalized mutual information, joint entropy, and Hill’s third moment.
KW - Artifact pattern
KW - Artifact reduction
KW - Image registration
KW - Interpolation artifacts
KW - Multi-modality
KW - Mutual information
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UR - http://www.scopus.com/inward/citedby.url?scp=84967373584&partnerID=8YFLogxK
U2 - 10.1142/9789812705785_0008
DO - 10.1142/9789812705785_0008
M3 - Chapter
SN - 9812563644
SN - 9789812569936
SP - 255
EP - 295
BT - Medical Imaging Systems Technology: Analysis and Computational Methods
PB - World Scientific Publishing Co.
ER -