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Magnetic Resonance Imaging: Recording, Reconstruction and Assessment [Mīkstie vāki]

(Professor, Department of Electronics and Instrumentation Engineering, St. Josephs College of Engineering, Chennai, Tamilnadu, India), (Associate Professor, Department of Computer Science and Engineering, Techno International New Town, )
  • Formāts: Paperback / softback, 188 pages, height x width: 235x191 mm, weight: 410 g, Approx. 200 illustrations (200 in full color); Illustrations
  • Sērija : Primers in Biomedical Imaging Devices and Systems
  • Izdošanas datums: 17-Feb-2022
  • Izdevniecība: Academic Press Inc
  • ISBN-10: 0128234016
  • ISBN-13: 9780128234013
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  • Mīkstie vāki
  • Cena: 102,77 €
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  • Formāts: Paperback / softback, 188 pages, height x width: 235x191 mm, weight: 410 g, Approx. 200 illustrations (200 in full color); Illustrations
  • Sērija : Primers in Biomedical Imaging Devices and Systems
  • Izdošanas datums: 17-Feb-2022
  • Izdevniecība: Academic Press Inc
  • ISBN-10: 0128234016
  • ISBN-13: 9780128234013
Citas grāmatas par šo tēmu:

Magnetic Resonance Imaging: Recording, Reconstruction and Assessment gives a detailed overview of magnetic resonance imaging (MRI), along with its applications and challenges. The book explores the abnormalities in internal human organs using MRI techniques while also featuring case studies that illustrate measures used. In addition, it explores precautionary measures used during MRI based imaging, the selection of appropriate contrast agents, and the selection of the appropriate modality during the image registration. Sections introduce medical imaging, the use of MRI in brain, cardiac, lung and kidney detection, and also discuss both 2D and 3D imaging techniques and various MRI modalities.

This volume will be of interest to researchers, engineers and medical professionals involved in the development and use of MRI systems.

  • Discusses challenges and issues faced, as well as safety precautions to be followed
  • Features case studies with benchmark MRIs existing in the literature
  • Introduces computer-based assessment (Machine Learning and Deep Learning) of the MRI based on its 2D slices
Preface vii
1 Introduction to image-assisted disease screening
1(28)
1.1 Introduction
1(2)
1.2 Acute diseases in vital organs
3(19)
1.3 Discussion of the need for an imaging scheme
22(1)
1.4 Summary
23(6)
References
23(4)
Further reading
27(2)
2 Magnetic resonance imaging: recording and reconstruction
29(20)
2.1 Introduction
29(2)
2.2 MRI recording protocol
31(9)
2.3 Verification and validation
40(1)
2.4 Comparison of MRI modalities
41(3)
2.5 Summary
44(5)
References
44(5)
3 Image processing methods to enhance disease information in MRI slices
49(34)
3.1 Introduction
49(1)
3.2 Improvement methods for MRI slices
50(28)
3.3 Summary
78(5)
References
79(4)
4 A study of the segmentation of tumor in breast MRI using entropy thresholding and the Mayfly algorithm
83(22)
4.1 Introduction
83(1)
4.2 Related research m
84(1)
4.3 Methodology
85(10)
4.4 Result and discussion
95(6)
4.5 Conclusion
101(4)
References
101(4)
5 Abnormality detection in heart MRI with spotted hyena algorithm-supported Kapur/Otsu thresholding and level set segmentation
105(22)
5.1 Introduction
105(2)
5.2 Related research work
107(1)
5.3 Methodology
107(9)
5.4 Results and discussion
116(8)
5.5 Conclusion
124(3)
References
125(2)
6 CNN-based segmentation of brain tumor from T2-weighted MRI slices
127(20)
6.1 Introduction
127(2)
6.2 Related research
129(1)
6.3 Methodology
129(7)
6.4 Results and discussion
136(7)
6.5 Conclusion
143(4)
References
143(4)
7 Automated detection of ischemic stroke with brain MRI using machine learning and deep learning features
147(28)
7.1 Introduction
147(2)
7.2 Earlier research
149(1)
7.3 Methodology
149(6)
7.4 Experimental results
155(9)
7.5 Discussion
164(7)
7.6 Conclusion
171(4)
References
172(3)
Index 175
Professor V. Rajinikanth works in the Department of Electronics and Instrumentation Engineering at St. Josephs College of Engineering in Chennai, Tamilnadu, India. Nilanjan Dey (Senior Member, IEEE) received the B.Tech., M.Tech. in information technology from West Bengal Board of Technical University and Ph.D. degrees in electronics and telecommunication engineering from Jadavpur University, Kolkata, India, in 2005, 2011, and 2015, respectively. Currently, he is Associate Professor with the Techno International New Town, Kolkata and a visiting fellow of the University of Reading, UK. He has authored over 300 research articles in peer-reviewed journals and international conferences and 40 authored books. His research interests include medical imaging and machine learning. Moreover, he actively participates in program and organizing committees for prestigious international conferences, including World Conference on Smart Trends in Systems Security and Sustainability (WorldS4), International Congress on Information and Communication Technology (ICICT), International Conference on Information and Communications Technology for Sustainable Development (ICT4SD) etc.

He is also the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, Associate Editor of IEEE Transactions on Technology and Society and series Co-Editor of Springer Tracts in Nature-Inspired Computing and Data-Intensive Research from Springer Nature and Advances in Ubiquitous Sensing Applications for Healthcare from Elsevier etc. Furthermore, he was an Editorial Board Member Complex & Intelligence Systems, Springer, Applied Soft Computing, Elsevier and he is an International Journal of Information Technology, Springer, International Journal of Information and Decision Sciences etc. He is a Fellow of IETE and member of IE, ISOC etc.