Deep Learning Models for Medical Imaging /

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...

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Bibliographic Details
Main Authors: Santosh, K. C., author 651156, Das, Nibaran, 1981-, author 651157, Ghosh, Swarnendu, author 651158, ScienceDirect (Online service) 7722
Format: software, multimedia
Language:eng
Published: London : Academic Press, 2021
Subjects:
Online Access:https://www.sciencedirect.com/science/book/9780128235041
Description
Summary: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.