Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Medical Imaging 2009 - Image Processing |
| Publikationsstatus | Veröffentlicht - 27 März 2009 |
| Veranstaltung | Medical Imaging 2009 - Image Processing - Lake Buena Vista, FL, USA / Vereinigte Staaten Dauer: 8 Feb. 2009 → 10 Feb. 2009 |
Publikationsreihe
| Name | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
|---|---|
| Band | 7259 |
| ISSN (Print) | 1605-7422 |
Abstract
Respiration-induced organ motion can limit the accuracy required for many clinical applications working on the thorax or upper abdomen. One approach to reduce the uncertainty of organ location caused by respiration is to use prior knowledge of breathing motion. In this work, we deal with the extraction and modeling of lung motion fields based on free-breathing 4D-CT data sets of 36 patients. Since data was acquired for radiotherapy planning, images of the same patient were available over different weeks of treatment. Motion field extraction is performed using an iterative shape-constrained deformable model approach. From the extracted motion fields, intra- and inter-subject motion models are built and adapted in a leave-one-out test. The created models capture the motion of corresponding landmarks over the breathing cycle. Model adaptation is then performed by examplarily assuming the diaphragm motion to be known. Although, respiratory motion shows a repetitive character, it is known that patients' variability in breathing pattern impedes motion estimation. However, with the created motion models, we obtained a mean error between the phases of maximal distance of 3.4 mm for the intra-patient and 4.2 mm for the inter-patient study when assuming the diaphragm motion to be known.
ASJC Scopus Sachgebiete
- Werkstoffwissenschaften (insg.)
- Elektronische, optische und magnetische Materialien
- Werkstoffwissenschaften (insg.)
- Biomaterialien
- Physik und Astronomie (insg.)
- Atom- und Molekularphysik sowie Optik
- Medizin (insg.)
- Radiologie, Nuklearmedizin und Bildgebung
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- BibTex
- RIS
Medical Imaging 2009 - Image Processing. 2009. 72590T (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Band 7259).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Free-Breathing Intra- and Intersubject Respiratory Motion Capturing, Modeling, and Prediction
AU - Klinder, Tobias
AU - Lorenz, Cristian
AU - Ostermann, Jörn
PY - 2009/3/27
Y1 - 2009/3/27
N2 - Respiration-induced organ motion can limit the accuracy required for many clinical applications working on the thorax or upper abdomen. One approach to reduce the uncertainty of organ location caused by respiration is to use prior knowledge of breathing motion. In this work, we deal with the extraction and modeling of lung motion fields based on free-breathing 4D-CT data sets of 36 patients. Since data was acquired for radiotherapy planning, images of the same patient were available over different weeks of treatment. Motion field extraction is performed using an iterative shape-constrained deformable model approach. From the extracted motion fields, intra- and inter-subject motion models are built and adapted in a leave-one-out test. The created models capture the motion of corresponding landmarks over the breathing cycle. Model adaptation is then performed by examplarily assuming the diaphragm motion to be known. Although, respiratory motion shows a repetitive character, it is known that patients' variability in breathing pattern impedes motion estimation. However, with the created motion models, we obtained a mean error between the phases of maximal distance of 3.4 mm for the intra-patient and 4.2 mm for the inter-patient study when assuming the diaphragm motion to be known.
AB - Respiration-induced organ motion can limit the accuracy required for many clinical applications working on the thorax or upper abdomen. One approach to reduce the uncertainty of organ location caused by respiration is to use prior knowledge of breathing motion. In this work, we deal with the extraction and modeling of lung motion fields based on free-breathing 4D-CT data sets of 36 patients. Since data was acquired for radiotherapy planning, images of the same patient were available over different weeks of treatment. Motion field extraction is performed using an iterative shape-constrained deformable model approach. From the extracted motion fields, intra- and inter-subject motion models are built and adapted in a leave-one-out test. The created models capture the motion of corresponding landmarks over the breathing cycle. Model adaptation is then performed by examplarily assuming the diaphragm motion to be known. Although, respiratory motion shows a repetitive character, it is known that patients' variability in breathing pattern impedes motion estimation. However, with the created motion models, we obtained a mean error between the phases of maximal distance of 3.4 mm for the intra-patient and 4.2 mm for the inter-patient study when assuming the diaphragm motion to be known.
KW - 4D-CT
KW - Motion estimation
KW - Motion modeling
KW - Respiratory motion
UR - http://www.scopus.com/inward/record.url?scp=71649106931&partnerID=8YFLogxK
U2 - 10.1117/12.811990
DO - 10.1117/12.811990
M3 - Conference contribution
AN - SCOPUS:71649106931
SN - 9780819475107
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2009 - Image Processing
T2 - Medical Imaging 2009 - Image Processing
Y2 - 8 February 2009 through 10 February 2009
ER -