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Deep Learning Models for Medical Imaging

1st Edition - September 7, 2021

Authors: KC Santosh, Nibaran Das, Swarnendu Ghosh

Paperback ISBN:
9 7 8 - 0 - 1 2 - 8 2 3 5 0 4 - 1
eBook ISBN:
9 7 8 - 0 - 1 2 - 8 2 3 6 5 0 - 5

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)… Read more

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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.