Deep Learning Models for Medical Imaging

Deep Learning Models for Medical Imaging

1st Edition - September 7, 2021

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  • Authors: KC Santosh, Nibaran Das, Swarnendu Ghosh
  • Paperback ISBN: 9780128235041
  • eBook ISBN: 9780128236505

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Description

Deep Learning Models for Medical Imaging explains the concepts of Deep Learning (DL) and its importance in medical imaging and/or healthcare using two different case studies: a) cytology image analysis and b) coronavirus (COVID-19) prediction, screening, and decision-making, using publicly available datasets in their respective experiments. Of many DL models, custom Convolutional Neural Network (CNN), ResNet, InceptionNet and DenseNet are used. The results follow ‘with’ and ‘without’ transfer learning (including different optimization solutions), in addition to the use of data augmentation and ensemble networks. DL models for medical imaging are suitable for a wide range of readers starting from early career research scholars, professors/scientists to industrialists.

Key Features

  • Provides a step-by-step approach to develop deep learning models
  • Presents case studies showing end-to-end implementation (source codes: available upon request)

Readership

Engineers and biomedical engineers, medical imaging researchers and graduate students

Table of Contents

  • 1. Introduction
    KC Santosh, Nibaran Das, and Swarnendu Ghosh
    2. Deep learning: a review
    KC Santosh, Nibaran Das, and Swarnendu Ghosh
    3. Deep learning models
    KC Santosh, Nibaran Das, and Swarnendu Ghosh
    4. Cytology image analysis
    KC Santosh, Nibaran Das, and Swarnendu Ghosh
    5. COVID-19: prediction, screening, and decision-making
    KC Santosh, Nibaran Das, and Swarnendu Ghosh

Product details

  • No. of pages: 170
  • Language: English
  • Copyright: © Academic Press 2021
  • Published: September 7, 2021
  • Imprint: Academic Press
  • Paperback ISBN: 9780128235041
  • eBook ISBN: 9780128236505

About the Authors

KC Santosh

Prof. KC Santosh is the Chair of the Department of Computer Science at the University of South Dakota (USD). Before joining USD, Prof. Santoshworked as a research fellow at the U.S. National Library of Medicine (NLM), National Institutes of Health (NIH). He was a postdoctoral research scientist at the LORIA research centre (with industrial partner, ITESOFT (France)). He has demonstrated expertise in artificial intelligence, machine learning, pattern recognition, computer vision, image processing and data mining with applications, such as medical imaging informatics, document imaging, biometrics, forensics, and speech analysis. His research projects are funded by multiple agencies, such as SDCRGP, Department of Education, National Science Foundation, and Asian Office of Aerospace Research and Development. He is the proud recipient of the Cutler Award for Teaching and Research Excellence (USD, 2021), the President’s Research Excellence Award (USD, 2019), and the Ignite Award from the U.S. Department

Affiliations and Expertise

KC’s PAMI: Pattern Analysis & Machine Intelligence Research Lab - Department of Computer Science, University of South Dakota, USA

Nibaran Das

Nibaran Das received his B.Tech degree in Computer Science and Technology from Kalyani Govt. Engineering College under KalyaniUniversity, in 2003. He received his M.C.S.E. degree from Jadavpur University, in 2005. He received his Ph.D. (Engg.) degree thereafter from Jadavpur University, in 2012. He joined J.U. as a lecturer in 2006. His areas of current research interest are OCR of handwritten text, optimization techniques, image processing, and deep learning. He has been an editor of Bengali monthly magazine Computer Jagat since 2005.

Affiliations and Expertise

Department of Computer Science and Engineering, Jadavpur University, Kolkota, India

Swarnendu Ghosh

Swarnendu Ghosh is an Assistant Professor at Adamas University in the department of Computer Science and Engineering. He received his B.Tech degree in Computer Science and Engineering from West Bengal University of Technology, in 2012. He received his Masters in Computer Science and Engineering from Jadavpur University, in 2014. He has been a doctoral fellow under the Erasmus Mundus Mobility with Asia at University of Evora, Portugal. Currently he is continuing his Ph.D. on Computer Science and Engineering at Jadavpur University. His area of interest is deep learning, graph based learning, and knowledge representation.

Affiliations and Expertise

Jadavpur University, Kolkota, India

Ratings and Reviews

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  • Kathy D. Thu Mar 10 2022

    Heavy technical book

    Enjoyed the book and those applications - this book, I would recommend University Libraries to consider as reference books for computer science, health informatics, and biomedical engineering departments, to name a few.

  • Nupur Mon Feb 21 2022

    Best book for understanding medical imaging

    Best book, where authors write solidly for medical imaging problems using deep learning models. Book could possibly be used for industry as well. Research scholars will be benefiting from this book, for sure. I truly enjoyed the book.

  • George N. Mon Nov 22 2021

    Technically sound book - well written

    Well-written technically sound book: authors did really show their mileage in terms of writing (technical) with multiple applications. I, personally, love Covid-19 chapter, where authors discussed on the use of prediction, screening, and decision-making. Hats off to authors - well done!