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The Resource 4D Modeling and Estimation of Respiratory Motion for Radiation Therapy, edited by Jan Ehrhardt, Cristian Lorenz, (electronic resource)

4D Modeling and Estimation of Respiratory Motion for Radiation Therapy, edited by Jan Ehrhardt, Cristian Lorenz, (electronic resource)

Label
4D Modeling and Estimation of Respiratory Motion for Radiation Therapy
Title
4D Modeling and Estimation of Respiratory Motion for Radiation Therapy
Statement of responsibility
edited by Jan Ehrhardt, Cristian Lorenz
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Contributor
Editor
Subject
Language
eng
Summary
Respiratory motion causes an important uncertainty in radiotherapy planning of the thorax and upper abdomen. The main objective of radiation therapy is to eradicate or shrink tumor cells without damaging the surrounding tissue by delivering a high radiation dose to the tumor region and a dose as low as possible to healthy organ tissues. Meeting this demand remains a challenge especially in case of lung tumors due to breathing-induced tumor and organ motion where motion amplitudes can measure up to several centimeters. Therefore, modeling of respiratory motion has become increasingly important in radiation therapy. With 4D imaging techniques spatiotemporal image sequences can be acquired to investigate dynamic processes in the patient{u2019}s body. Furthermore, image registration enables the estimation of the breathing-induced motion and the description of the temporal change in position and shape of the structures of interest by establishing the correspondence between images acquired at different phases of the breathing cycle. In radiation therapy these motion estimations are used to define accurate treatment margins, e.g. to calculate dose distributions and to develop prediction models for gated or robotic radiotherapy. In this book, the increasing role of image registration and motion estimation algorithms for the interpretation of complex 4D medical image sequences is illustrated. Different 4D CT image acquisition techniques and conceptually different motion estimation algorithms are presented. The clinical relevance is demonstrated by means of example applications which are related to the radiation therapy of thoracic and abdominal tumors. The state of the art and perspectives are shown by an insight into the current field of research. The book is addressed to biomedical engineers, medical physicists, researchers and physicians working in the fields of medical image analysis, radiology and radiation therapy
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0
Literary form
non fiction
Series statement
Biological and Medical Physics, Biomedical Engineering,
4D Modeling and Estimation of Respiratory Motion for Radiation Therapy, edited by Jan Ehrhardt, Cristian Lorenz, (electronic resource)
Label
4D Modeling and Estimation of Respiratory Motion for Radiation Therapy, edited by Jan Ehrhardt, Cristian Lorenz, (electronic resource)
Link
http://libproxy.rpi.edu/login?url=http://dx.doi.org/10.1007/978-3-642-36441-9
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Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
4D Image Acquisition -- Motion Estimation and Modeling -- Modeling of Motion Variability -- Applications of Motion Estimation Algorithms -- Outlook
http://library.link/vocab/cover_art
https://contentcafe2.btol.com/ContentCafe/Jacket.aspx?Return=1&Type=S&Value=9783642364419&userID=ebsco-test&password=ebsco-test
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unknown
http://library.link/vocab/discovery_link
{'f': 'http://opac.lib.rpi.edu/record=b3394519'}
Extent
XX, 341 p. 111 illus., 75 illus. in color.
File format
multiple file formats
Form of item
electronic
Isbn
9783642364419
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote

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