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Author Abidi, Ali Imam., author. Author. http://id.loc.gov/vocabulary/relators/aut.
Title Deformable Registration Techniques for Thoracic CT Images : An Insight into Medical Image Registration / by Ali Imam Abidi, S.K. Singh.
Edition First edition 2020.
OCLC 978-981-10-5837-0
ISBN 9789811058370
ISBN/ISSN 10.1007/978-981-10-5837-0 doi
Publisher Singapore : Springer Singapore : Imprint: Springer, 2020.
Description VII, 135 pages 83 illustrations, 18 illustrations in color. : online resource
text file PDF rda
LC Subject heading/s Optical data processing.
Pattern perception.
Radiology.
Bioinformatics¡.
Computational biology¡.
Medical informatics.
Computer graphics.
Other
Subject heading/s		 Image Processing and Computer Vision. https://scigraph.springernature.com/ontologies/product-market-codes/I22021
Pattern Recognition. https://scigraph.springernature.com/ontologies/product-market-codes/I2203X
Imaging / Radiology. https://scigraph.springernature.com/ontologies/product-market-codes/H29005
Computer Appl. in Life Sciences. https://scigraph.springernature.com/ontologies/product-market-codes/L17004
Health Informatics. https://scigraph.springernature.com/ontologies/product-market-codes/I23060
Computer Graphics. https://scigraph.springernature.com/ontologies/product-market-codes/I22013
Contents Chapter 1. Introduction -- Chapter 2. Theoretical Background -- Chapter 3. A Moving Least Square Based Framework for Thoracic CT Image Registration -- Chapter 4. A Path Tracing and Deformity Estimation Methodology for Registration of Thoracic CT Image Sequences -- Chapter 5. Deformable Thoracic CT Images Sequence Registration using Strain Energy Minimization -- Chapter 6. Conclusion & Future Work.
Summary This book focuses on novel approaches for thoracic computed tomography (CT) image registration and determination of respiratory motion models in a range of patient scenarios. It discusses the use of image registration processes to remove the inconsistencies between medical images acquired using different devices. In the context of comparative research and medical analysis, these methods are of immense value in image registration procedures, not just for thoracic CT images, but for all types of medical images in multiple modalities, and also in establishing a mean respiration motion model. Combined with advanced techniques, the methods proposed have the potential to advance the field of computer vision and help improve existing methods. The book is a valuable resource for those in the scientific community involved in modeling respiratory motion for a large number of people. .
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