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.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Biswas, Mainak (Editor ), Suri, Jasjit S. (Editor )
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:
Diagnostic imaging > Data processing.
Deep learning (Machine learning)
Computer vision.
Diagnostic Imaging.
Deep Learning.
Visual Perception.
Biomedical engineering.
TECHNOLOGY & ENGINEERING / Biomedical.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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.

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