Description

Book Synopsis

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 (CNN), deep belief networks (DBN), autoencoders, residual neural networks (Res Nets). The text discusses some of the Deep Learning-based applications in gene identification. Sections in the book explore the foundation and necessity of deep learning in radiology, the application of deep learning in the area of cardiovascular imaging and deep learning applications in the area of fatty liver disease characterization and COVID19, respectively.


This reference text is highly relevant for medical professionals and researchers in the area of AI in medical imaging.

 

Key Features:


  • Discusses various diseases related to lung, heart, peripheral arterial imaging, as well as gene expression characterization and classification


  • Explo

Multimodality Imaging Volume 1

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    A Hardback by Jasjit Suri, Professor Mainak Biswas

    £108.00

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    RRP £120.00 – you save £12.00 (10%)

    Order before 4pm tomorrow for delivery by Fri 23 Oct 2026.

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      Book details

      Published 12/20/2022 12:00:00 AM
      ISBN-13 9780750322423
      978-0750322423
      ISBN-10 075032242X

      Description

      Book Synopsis

      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 (CNN), deep belief networks (DBN), autoencoders, residual neural networks (Res Nets). The text discusses some of the Deep Learning-based applications in gene identification. Sections in the book explore the foundation and necessity of deep learning in radiology, the application of deep learning in the area of cardiovascular imaging and deep learning applications in the area of fatty liver disease characterization and COVID19, respectively.


      This reference text is highly relevant for medical professionals and researchers in the area of AI in medical imaging.

       

      Key Features:


      • Discusses various diseases related to lung, heart, peripheral arterial imaging, as well as gene expression characterization and classification


      • Explo

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