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Deformable Registration Techniques for Thoracic CT Images: An Insight Into Medical Image Registration

ISBN-13: 9789811058363 / Angielski / Twarda / 2020 / 135 str.

Ali Abidi; S. K. Singh
Deformable Registration Techniques for Thoracic CT Images: An Insight Into Medical Image Registration Abidi, Ali Imam 9789811058363 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Deformable Registration Techniques for Thoracic CT Images: An Insight Into Medical Image Registration

ISBN-13: 9789811058363 / Angielski / Twarda / 2020 / 135 str.

Ali Abidi; S. K. Singh
cena 402,53
(netto: 383,36 VAT:  5%)

Najniższa cena z 30 dni: 385,52
Termin realizacji zamówienia:
ok. 22 dni roboczych
Dostawa w 2026 r.

Darmowa dostawa!

In the field 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 varieties of medical images in multiple modalities, and also in establishing a mean respiration motion model.

Kategorie:
Informatyka
Kategorie BISAC:
Computers > Software Development & Engineering - Computer Graphics
Computers > Artificial Intelligence - Computer Vision & Pattern Recognition
Medical > Biochemistry
Wydawca:
Springer
Język:
Angielski
ISBN-13:
9789811058363
Rok wydania:
2020
Wydanie:
2020
Ilość stron:
135
Waga:
0.36 kg
Wymiary:
23.88 x 19.3 x 1.27
Oprawa:
Twarda
Wolumenów:
01

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.

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.

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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