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Deformable Registration Techniques for Thoracic CT Images

An Insight into Medical Image Registration

  • Book
  • © 2020

Overview

Authors:
  1. Ali Imam Abidi

    1. Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, India

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  2. S.K. Singh

    1. Department of Computer Science and Engineering, Indian Institute of Technology, BHU, Varanasi, India

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    You can also search for this author in PubMed   Google Scholar

  • Helps the scientific community model respiratory motion for a large number of people
  • Presents a universal baseline that will attract more and more datasets and findings from around the globe
  • Serves as a common repository of related research
  • Discusses the process of image registration to remove the inconsistencies between medical images acquired using different devices

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Table of contents (6 chapters)

  1. Front Matter

    Pages i-vii
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  2. Introduction

    • Ali Imam Abidi, S. K. Singh
    Pages 1-13

  3. Theoretical Background

    • Ali Imam Abidi, S. K. Singh
    Pages 15-40

  4. A Moving Least Square Based Framework for Thoracic CT Image Registration

    • Ali Imam Abidi, S. K. Singh
    Pages 41-53

  5. A Path Tracing and Deformity Estimation Methodology for Registration of Thoracic CT Image Sequences

    • Ali Imam Abidi, S. K. Singh
    Pages 55-76

  6. Deformable Thoracic CT Images Sequence Registration Using Strain Energy Minimization

    • Ali Imam Abidi, S. K. Singh
    Pages 77-90

  7. Conclusion and Future Work

    • Ali Imam Abidi, S. K. Singh
    Pages 91-92

  8. Back Matter

    Pages 93-135
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Keywords

About this book

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. 

Authors and Affiliations

  • Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, India

    Ali Imam Abidi

  • Department of Computer Science and Engineering, Indian Institute of Technology, BHU, Varanasi, India

    S.K. Singh

About the authors

Dr. Ali Imam Abidi is an Assistant Professor at the Department of Computer Science & Engineering, School of Engineering & Technology, Sharda University. He received his Ph.D. from the Department of Computer Science and Engineering, Indian Institute of Technology, Banaras Hindu University (IIT-BHU), Varanasi, India. His primary areas of research include (but is not limited to) deformable image registration, image feature data analysis etc. as well as the study and applications of behavioural design concepts. He has published numerous research articles, letters, papers in conference proceedings and book chapters. He has been a constant invited reviewer for reputed journals like MTAP, MBEC, NAS Letters etc

  
Prof. Sanjay Kumar Singh holds a B.Tech. in Computer Engineering, M.Tech. in Computer Applications and a Ph.D. in Computer Science and Engineering. Currently, he is a Professor at the Department of Computer Science and Engineering, Indian Institute of Technology, Banaras Hindu University (IIT-BHU), Varanasi, India, and is also a Certified Novell Engineer Administrator. He is a member of LIMSTE, the Institute of Electrical and Electronics Engineers (IEEE), the International Association of Engineers (IAENG) and the International Center of Sustainable Excellence (ISCE). His research areas include biometrics, computer vision, image processing, video processing, pattern recognition and artificial intelligence. He has published over 50 articles in national and international journals, as well as book chapters and conference papers.

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