Main description:

Provides a comprehensive overview of machine learning and deep learning techniques for biomedical imaging
Includes thoracic imaging, abdominal imaging, brain imaging, and retinal imaging
Covers new and emerging methods in machine learning
Features contributions from leading experts
Presents tools to improve computer aided diagnosis

Contents:

Preface. Acknowledgements. Editors. Contributors. Chapter 1 Another Set of Eyes in Anesthesiology. Chapter 2 Dermatological Machine Learning Clinical Decision Support System. Chapter 3 Vision and AI. Chapter 4 Thermal Dose Modeling for Thermal Ablative Cancer Treatments by Cellular Neural Networks. Chapter 5 Ensembles of Convolutional Neural Networks with Different Activation Functions for Small to Medium-Sized Biomedical Datasets. Chapter 6 Analysis of Structural MRI Data for Epilepsy Diagnosis Using Machine Learning Techniques. Chapter 7 Artificial Intelligence-Powered Ultrasound for Diagnosis and Improving Clinical Workflow. Chapter 8 Machine Learning for E/MEG-Based Identification of Alzheimer's Disease. Chapter 9 Some Practical Challenges with Possible Solutions for Machine Learning in Medical Imaging. Chapter 10 Detection of Abnormal Activities Stemming from Cognitive Decline Using Deep Learning. Chapter 11 Classification of Left Ventricular Hypertrophy and NAFLD through Decision Tree Algorithm. Chapter 12 The Cutting Edge of Surgical Practice: Applications of Machine Learning to Neurosurgery. Chapter 13 A Novel MRA-Based Framework for the Detection of Cerebrovascular Changes and Correlation to Blood Pressure. Chapter 14 Early Classification of Renal Rejection Types: A Deep Learning Approach. Index.