Details
| Original language | English |
|---|---|
| Title of host publication | Medical Imaging 2009 - Image Processing |
| Publication status | Published - 27 Mar 2009 |
| Event | Medical Imaging 2009 - Image Processing - Lake Buena Vista, FL, United States Duration: 8 Feb 2009 → 10 Feb 2009 |
Publication series
| Name | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
|---|---|
| Volume | 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.
Keywords
- 4D-CT, Motion estimation, Motion modeling, Respiratory motion
ASJC Scopus subject areas
- Materials Science(all)
- Electronic, Optical and Magnetic Materials
- Materials Science(all)
- Biomaterials
- Physics and Astronomy(all)
- Atomic and Molecular Physics, and Optics
- Medicine(all)
- Radiology Nuclear Medicine and imaging
Cite this
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- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
Medical Imaging 2009 - Image Processing. 2009. 72590T (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 7259).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › 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 -