Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Society of Photo-Optical Instrumentation Engineers (SPIE) Medical Imaging 2014 |
| Publisher | SPIE |
| ISBN (print) | 9780819498274 |
| Publication status | Published - 2014 |
| Event | Medical Imaging 2014: Image Processing - San Diego, CA, United States Duration: 16 Feb 2014 → 18 Feb 2014 |
Publication series
| Name | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
|---|---|
| Volume | 9034 |
| ISSN (Print) | 1605-7422 |
Abstract
In recent years, optical coherence tomography (OCT) has gained increasing attention not only as an imaging device, but also as a navigation system for surgical interventions. This approach demands to register intraoperative OCT to pre-operative computed tomography (CT) data. In this study, we evaluate algorithms for multi-modal image registration of OCT and CT data of a human temporal bone specimen. We focus on similarity measures that are common in this field, e.g., normalized mutual information, normalized cross correlation, and iterative closest point. We evaluate and compare their accuracies to the relatively new normal distribution transform (NDT), that is very common in simultaneous localization and mapping applications, but is not widely used in image registration. Matching is realized considering appropriate image pre-processing, the aforementioned similarity measures, and local optimization algorithms, as well as line search optimization. For evaluation purpose, the results of a point-based registration with fiducial landmarks are regarded as ground truth. First results indicate that state of the art similarity functions do not perform with the desired accuracy, when applied to unprocessed image data. In contrast, NDT seems to achieve higher registration accuracy.
Keywords
- Computed tomography, Multi-modal image registration, Navigation, Optical coherence tomography, Similarity measures
ASJC Scopus subject areas
- Materials Science(all)
- Electronic, Optical and Magnetic Materials
- Physics and Astronomy(all)
- Atomic and Molecular Physics, and Optics
- Materials Science(all)
- Biomaterials
- Medicine(all)
- Radiology Nuclear Medicine and imaging
Cite this
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Proceedings of the Society of Photo-Optical Instrumentation Engineers (SPIE) Medical Imaging 2014. SPIE, 2014. 90343L (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9034).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Normal distributions transform in multi-modal image registration of optical coherence tomography and computed tomography datasets
AU - Díaz, Jesús Díaz
AU - Riva, Mauro H.
AU - Majdani, Omid
AU - Ortmaier, Tobias
PY - 2014
Y1 - 2014
N2 - In recent years, optical coherence tomography (OCT) has gained increasing attention not only as an imaging device, but also as a navigation system for surgical interventions. This approach demands to register intraoperative OCT to pre-operative computed tomography (CT) data. In this study, we evaluate algorithms for multi-modal image registration of OCT and CT data of a human temporal bone specimen. We focus on similarity measures that are common in this field, e.g., normalized mutual information, normalized cross correlation, and iterative closest point. We evaluate and compare their accuracies to the relatively new normal distribution transform (NDT), that is very common in simultaneous localization and mapping applications, but is not widely used in image registration. Matching is realized considering appropriate image pre-processing, the aforementioned similarity measures, and local optimization algorithms, as well as line search optimization. For evaluation purpose, the results of a point-based registration with fiducial landmarks are regarded as ground truth. First results indicate that state of the art similarity functions do not perform with the desired accuracy, when applied to unprocessed image data. In contrast, NDT seems to achieve higher registration accuracy.
AB - In recent years, optical coherence tomography (OCT) has gained increasing attention not only as an imaging device, but also as a navigation system for surgical interventions. This approach demands to register intraoperative OCT to pre-operative computed tomography (CT) data. In this study, we evaluate algorithms for multi-modal image registration of OCT and CT data of a human temporal bone specimen. We focus on similarity measures that are common in this field, e.g., normalized mutual information, normalized cross correlation, and iterative closest point. We evaluate and compare their accuracies to the relatively new normal distribution transform (NDT), that is very common in simultaneous localization and mapping applications, but is not widely used in image registration. Matching is realized considering appropriate image pre-processing, the aforementioned similarity measures, and local optimization algorithms, as well as line search optimization. For evaluation purpose, the results of a point-based registration with fiducial landmarks are regarded as ground truth. First results indicate that state of the art similarity functions do not perform with the desired accuracy, when applied to unprocessed image data. In contrast, NDT seems to achieve higher registration accuracy.
KW - Computed tomography
KW - Multi-modal image registration
KW - Navigation
KW - Optical coherence tomography
KW - Similarity measures
UR - http://www.scopus.com/inward/record.url?scp=84902096299&partnerID=8YFLogxK
U2 - 10.1117/12.2043623
DO - 10.1117/12.2043623
M3 - Conference contribution
AN - SCOPUS:84902096299
SN - 9780819498274
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Proceedings of the Society of Photo-Optical Instrumentation Engineers (SPIE) Medical Imaging 2014
PB - SPIE
T2 - Medical Imaging 2014: Image Processing
Y2 - 16 February 2014 through 18 February 2014
ER -