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Multimodality imaging. Volume 1, Deep learning applications /
This research and reference text explores the finer details of deep learning models. It provides a brief outline on popular models including convolution neural networks, deep belief networks, autoencoders and residual neural networks.
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) :
IOP Publishing,
[2022]
|
| Colección: | IOP (Series). Release 22.
IOP ebooks. 2022 collection. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a Multimodality imaging. |n Volume 1, |p Deep learning applications / |c edited by Mainak Biswas, Jasjit S. Suri. |
| 264 | 1 | |a Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : |b IOP Publishing, |c [2022] | |
| 300 | |a 1 online resource (various pagings) : |b illustrations (some color). | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 490 | 1 | |a [IOP release $release] | |
| 490 | 1 | |a IOP ebooks. [2022 collection] | |
| 500 | |a "Version: 20221201"--Title page verso. | ||
| 504 | |a Includes bibliographical references. | ||
| 505 | 0 | |a part I. Deep learning and its applications. 1. Deep learning and augmented radiology / Mainak Biswas and Jasjit S. Suri -- 2. Deep learning in biomedical imaging / Mainak Biswas and Jasjit S. Suri | |
| 505 | 8 | |a part II. Deep learning in brain imaging. 3. A review of artificial intelligence in brain tumor classification and segmentation / Mainak Biswas and Jasjit S. Suri -- 4. MRI based brain tumor classification and its validation : a transfer learning paradigm / Luca Saba, Gopal S. Tandel, Mainak Biswas, Michele Porcu, N.N. Khanna, Monica Turk, Christopher K. Asare, Annabel A. Ankrah and Jasjit S. Suri | |
| 505 | 8 | |a 5. Magnetic resonance based Wilson's disease tissue characterization in an artificial intelligence framework using transfer learning / Siva Skandha, Luca Saba, Suneet K. Gupta, Vijaya K. Kumar, Amer M. Johri, Narendra N. Khanna, Sophie Mavrogeni, John R. Laird, Gyan Pareek, Petros P. Sfikakis, Athanasios Protogerou, Monica Turk, Aditya M. Sharma, Andrew Nicolaides, George D. Kitas, Klaudija Viskovic, Tomaz Omerzu and Jasjit S. Suri | |
| 505 | 8 | |a part III. Deep learning in cardiovascular imaging. 6. Artificial intelligence based carotid plaque tissue characterisation and classification from ultrasound images using a deep learning paradigm / Luca Saba, Sanagala S. Skandha, Suneet K. Gupta, Anudeep Puvvula, Vijaya K. Koppula, Amer M. Johri, Narendra N. Khanna, Sophie Mavrogeni, John R. Laird, Gyan Pareek, Martin Miner, Petros P. Sfikakis, Athanasios Protogerou, Durga P. Misra, Vikas Agarwal, Aditya M. Sharma, Vijay Viswanathan, Vijay S. Rathore, Monika Turk, Raghu Kolluri, Klaudija Viskovic, Elisa Cuadrado-Godia, George D. Kitas, Vijay Nambi, Deepak L. Bhatt, Andrew Nicolaides and Jasjit S. Suri -- 7. Quantification of plaque volume using a two-stage deep learning paradigm / Mainak Biswas and Jasjit S. Suri -- 8. Stenosis measurement from ultrasound carotid artery images in the deep learning paradigm / Mainak Biswas and Jasjit S. Suri -- 9. A systematic review of conventional and deep learning models for the measurement of plaque burden / Mainak Biswas and Jasjit S. Suri | |
| 505 | 8 | |a part IV. Machine and deep learning in liver imaging. 10. Ultrasound fatty liver disease risk stratification using an extreme learning machine framework / Mainak Biswas and Jasjit S. Suri -- 11. Symtosis : deep learning based liver ultrasound tissue characterisation and risk stratification / Mainak Biswas and Jasjit S. Suri | |
| 505 | 8 | |a part V. Deep learning in COVID-19. 12. Characterization of COVID-19 severity in infected lungs via artificial intelligence transfer learning / Sanagala S. Skandha, Luca Saba, Suneet K. Gupta, Vijaya K. Kumar, Amer M. Johri, Narendra N. Khanna, Sophie Mavrogeni, John R. Laird, Gyan Pareek, Petros P. Sfikakis, Athanasios Protogerou, Monica Turk, Aditya M. Sharma, Andrew Nicolaides, George D. Kitas, Klaudija Viskovic, Tomaz Omerzu and Jasjit S. Suri. | |
| 520 | 3 | |a This research and reference text explores the finer details of deep learning models. It provides a brief outline on popular models including convolution neural networks, deep belief networks, autoencoders and residual neural networks. | |
| 521 | |a Academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. | ||
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 538 | |a System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader. | ||
| 545 | |a Professor Mainak Biswas is a computer scientist with specialization in the application of machine learning and deep learning in biomedical domain. Professor Jasjit S. Suri has spent over 30 years in the field of biomedical engineering/sciences, software and hardware engineering and its management. | ||
| 588 | 0 | |a Title from PDF title page (viewed on January 9, 2023). | |
| 650 | 0 | |a Diagnostic imaging |x Data processing. | |
| 650 | 0 | |a Deep learning (Machine learning) | |
| 650 | 0 | |a Computer vision. | |
| 650 | 1 | 2 | |a Diagnostic Imaging. |
| 650 | 1 | 2 | |a Deep Learning. |
| 650 | 1 | 2 | |a Visual Perception. |
| 650 | 7 | |a Biomedical engineering. |2 bicssc | |
| 650 | 7 | |a TECHNOLOGY & ENGINEERING / Biomedical. |2 bisacsh | |
| 700 | 1 | |a Biswas, Mainak, |e editor. | |
| 700 | 1 | |a Suri, Jasjit S., |e editor. | |
| 710 | 2 | |a Institute of Physics (Great Britain), |e publisher. | |
| 776 | 0 | 8 | |i Print version: |z 9780750322423 |z 9780750322454 |
| 830 | 0 | |a IOP (Series). |p Release 22. | |
| 830 | 0 | |a IOP ebooks. |p 2022 collection. | |
| 856 | 4 | 0 | |u https://iopscience.uam.elogim.com/book/edit/978-0-7503-2244-7 |z Texto completo |