This book serves as source of introductory material and reference for medical application development and related technologies by providing the detailed implementation of the cutting-edge deep learning methodologies. It targets the cloud based advanced medical application developments using open-source python based deep learning libraries.
This book serves as source of introductory material and reference for medical application development and related technologies by providing the detailed implementation of the cutting-edge deep learning methodologies. It targets the cloud based advanced medical application developments using open-source python based deep learning libraries.
Snehan Biswas, is a Senior System Analyst in the department of Machine Learning and IoT, IEMA Research & Development Private Limited, India. He is a graduate in Electronics & Communication Engineering from University of Engineering and Management, Kolkata, India. His research interest includes Medical Image Processing, Machine Learning, Deep Learning, DevOps, Edge and Cloud computing. He has written several research articles in the field of Deep Learning, Machine learning, and Cloud Computing. Amartya Mukherjee, is Head of the Department in the Department of CSE(AIML), Institute of Engineering & Management, Kolkata, India. He is currently doing his research at the Maulana Abul Kalam Azad University of Technology, West Bengal, India. He holds a master's degree in Computer Science and Engineering from the NIT, Durgapur, West Bengal, India. His research interest includes Machine Learning, Deep Learning, IoT, Wireless communication, Sensor networks, healthcare. He has written many research articles and books in the domain of IoT, Machine learning, Bio medical systems, Sensor networks. Nilanjan Dey, is an Associate Professor in Department of Computer Science & Engineering at Techno International New Town, New Town, Kolkata, India. He is a visiting fellow of the University of Reading, UK. He is a Visiting Professor at Wenzhou Medical University, China and Duy Tan University, Vietnam, He was an honorary Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012-2015). He was awarded his PhD. from Jadavpur Univeristy in 2015. He has authored/edited more than 45 books with several reputed publishers, and published more than 300 papers. His main research interests include Medical Imaging, Machine learning, Computer Aided Diagnosis, Data Mining etc. He is the Indian Ambassador of International Federation for Information Processing (IFIP) - Young ICT Group. Recently, he has been awarded as one among the top 10 most published academics in the field of Computer Science in India (2015-17).
Inhaltsangabe
1. Introduction to different types of Medical Data and Image Analysis. 2. The Convolutional Neural Networks. 3. Detection of COVID 19 using a robust ensemble deep convolutional system incorporated with Inception V3 state of the art model and custom designed support Looping DCNN small. 4. Detection and Classification of Lung and Colon Cancer, via Histopathology data with ensemble Inception V3 and Looping DCNN large. 5. An Ensemble Deep Transfer Learning System for Classification and Detection of Malarial Cell Parasite. 6. Visualization of different categories of COVID 19 and Pneumonia X Ray image features by using a Deep Convolutional Auto Encoding Image Reconstruction Network (DCARN). 7. Medical X Ray images super resolution using Super Resolution Generative Adversarial Neural Network with Bi Modal Multi Perceptron Layers (SR GANN). 8. Conclusion.
1. Introduction to different types of Medical Data and Image Analysis. 2. The Convolutional Neural Networks. 3. Detection of COVID 19 using a robust ensemble deep convolutional system incorporated with Inception V3 state of the art model and custom designed support Looping DCNN small. 4. Detection and Classification of Lung and Colon Cancer, via Histopathology data with ensemble Inception V3 and Looping DCNN large. 5. An Ensemble Deep Transfer Learning System for Classification and Detection of Malarial Cell Parasite. 6. Visualization of different categories of COVID 19 and Pneumonia X Ray image features by using a Deep Convolutional Auto Encoding Image Reconstruction Network (DCARN). 7. Medical X Ray images super resolution using Super Resolution Generative Adversarial Neural Network with Bi Modal Multi Perceptron Layers (SR GANN). 8. Conclusion.
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