Deep Learning Applications in Medical Imaging

Deep Learning Applications in Medical Imaging

Indexed In: SCOPUS
Release Date: October, 2020|Copyright: © 2021 |Pages: 274
DOI: 10.4018/978-1-7998-5071-7
ISBN13: 9781799850717|ISBN10: 1799850714|EISBN13: 9781799850724
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Description & Coverage
Description:

Before the modern age of medicine, the chance of surviving a terminal disease such as cancer was minimal at best. After embracing the age of computer-aided medical analysis technologies, however, detecting and preventing individuals from contracting a variety of life-threatening diseases has led to a greater survival percentage and increased the development of algorithmic technologies in healthcare.

Deep Learning Applications in Medical Imaging is a pivotal reference source that provides vital research on the application of generating pictorial depictions of the interior of a body for medical intervention and clinical analysis. While highlighting topics such as artificial neural networks, disease prediction, and healthcare analysis, this publication explores image acquisition and pattern recognition as well as the methods of treatment and care. This book is ideally designed for diagnosticians, medical imaging specialists, healthcare professionals, physicians, medical researchers, academicians, and students.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Intelligence
  • Artificial Neural Networks
  • Computer-Aided Diagnosis
  • Critical Care
  • Disease Detection Techniques
  • Disease Prediction
  • Healthcare Analysis
  • Image Analysis
  • Machine Learning
  • Medical Data
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Editor/Author Biographies

Sanjay Saxena is an Assistant Professor in Department of Computer Science & Engineering, International Institute of Information Technology, Bhubaneswar, India. He has completed Ph.D. from Indian Institute of Technology (BHU), Varanasi, India in High Performance Medical Image Processing. Also, he completed Post Doctorate Research from Perelman School of Medicine, University of Pennsylvania, United States of America and worked on Brain Tumor (Glioblastoma) segmentation and analysis. He has published several research papers in peer reviewed international journals and conferences.

Sudip Paul is an Assistant Professor in the Department of Biomedical Engineering, School of Technology, North-Eastern Hill University, India since June 2012. He received his Ph.D degree from Indian Institute of Technology (Banaras Hindu University), Varanasi with specialization in Electrophysiology and brain signal analysis. He has also presented his research accomplishments in USA, Greece, France and South Africa. He has many credentials in his credit out of which his First Prize in Sushruta Innovation Award 2011 sponsored by Department of Science and Technology, Govt. of India and also he also organized co many workshops and conferences out of which most significant are the 29th Annual meeting of the Society for Neurochemistry, India and IRBO/APRC Associate School 2017. He was selected as Post Doc Fellow under Biotechnology Overseas Associateship 2017-18 supported by Department of Biotechnology, Government of India. He published more than 70 International journal and conference papers and also filled four patent. Recently he wrote two books published by LAP LAMBERT Academic Publishing, Germany and also published three book chapters in different international publishers.

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