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.

Contenu

Introduction to Medical Data and Image Analysis 2. The Convolutional Neural Network 3. The Detection of COVID-19 Pneumonia Using Inception V3 and Custom Designed Bi-Modal Looping DCNN via Analysis of X-Ray Images 4. Detection of Pneumonia from a Small-Scale Dataset of X-Ray Images of Lungs by Using a Compound Batch-Normalizing Convolutional Neural Feature Extracting Random Forest Classifier 5. An Adaptive Profound Transfer Learning Strategy for Malaria Cell Parasite Classification and Detection 6. Implementation of a Deep Convolutional Auto-Encoding Image-Reconstruction Network (DCARN) to Visualize Distinct Categories of COVID-19 and Pneumonia X-Ray Image Features 7. Super Resolution Generative Adversarial Neural Network (SR-GANN) with Bi-Modal Multi-Perceptron Layers for Medical X-Ray Images 8. Conclusion