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Deep Learning Models for Medical Imaging

Santosh, KC Das, Nibaran Ghosh, Swarnendu
Heftet / 2021 / Engelsk

Produktdetaljer

ISBN
9780128235041
Publisert
2021-09-08
Utgiver
Elsevier Science Publishing Co Inc
Vekt
360 gr
Høyde
235 mm
Bredde
191 mm
Aldersnivå
P, UP, 06, 05
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
170

Forfatter
Santosh, KC
Das, Nibaran
Ghosh, Swarnendu

Biografisk notat

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 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. 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.

Deep Learning Models for Medical Imaging

Santosh, KC Das, Nibaran Ghosh, Swarnendu
Heftet / 2021 / Engelsk
Santosh, KC Das, Nibaran Ghosh, Swarnendu
Heftet / 2021 / Engelsk
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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.
Les mer
1. Introduction 2. Deep learning: a review 3. Deep learning models 4. Cytology image analysis 5. COVID-19: prediction, screening, and decision-making
Helps readers learn and apply deep learning models to medical imaging
Provides a step-by-step approach to develop deep learning models Presents case studies showing end-to-end implementation (source codes: available upon request)

Relaterte produkter

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.
Les mer
1. Introduction 2. Deep learning: a review 3. Deep learning models 4. Cytology image analysis 5. COVID-19: prediction, screening, and decision-making
Helps readers learn and apply deep learning models to medical imaging
Provides a step-by-step approach to develop deep learning models Presents case studies showing end-to-end implementation (source codes: available upon request)

Produktdetaljer

ISBN
9780128235041
Publisert
2021-09-08
Utgiver
Elsevier Science Publishing Co Inc
Vekt
360 gr
Høyde
235 mm
Bredde
191 mm
Aldersnivå
P, UP, 06, 05
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
170

Forfatter
Santosh, KC
Das, Nibaran
Ghosh, Swarnendu

Biografisk notat

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 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. 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.

Relaterte produkter