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Deformable registration techniques f...
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Abidi, Ali Imam.
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Deformable registration techniques for thoracic CT images = an insight into medical image registration /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Deformable registration techniques for thoracic CT images/ by Ali Imam Abidi, S. K. Singh.
其他題名:
an insight into medical image registration /
作者:
Abidi, Ali Imam.
其他作者:
Singh, S. K.
出版者:
Singapore :Springer Singapore : : 2020.,
面頁冊數:
vii, 135 p. :ill., digital ;24 cm.
內容註:
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.
Contained By:
Springer eBooks
標題:
Chest - Imaging -
電子資源:
https://doi.org/10.1007/978-981-10-5837-0
ISBN:
9789811058370
Deformable registration techniques for thoracic CT images = an insight into medical image registration /
Abidi, Ali Imam.
Deformable registration techniques for thoracic CT images
an insight into medical image registration /[electronic resource] :by Ali Imam Abidi, S. K. Singh. - Singapore :Springer Singapore :2020. - vii, 135 p. :ill., digital ;24 cm.
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.
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.
ISBN: 9789811058370
Standard No.: 10.1007/978-981-10-5837-0doiSubjects--Topical Terms:
3524306
Chest
--Imaging
LC Class. No.: RC941 / .A253 2020
Dewey Class. No.: 617.540757
Deformable registration techniques for thoracic CT images = an insight into medical image registration /
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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.
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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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