Handbook of Deep Learning in Biomedical Engineering and Health Informatics: Biomedical Engineering: Techniques and Applications

ISBN-13: 9781771889988 / Angielski / Twarda / 2021 / 318 str.

E. Golden Julie; Y. Harold Robinson; S. M. Jaisakthi

Opis

This volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. It delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis.

Spis treści

1. Review of Existing Systems in Biomedical Using Deep Learning Algorithms 2. An Overview of Convolutional Neural Network Architecture and Its Variants in Medical Diagnostics of Cancer and COVID-19 3. Technical Assessment of Various Image Stitching Techniques: A Deep Learning Approach 4. CCNN: A Deep Learning Approach for an Acute Neurocutaneous Syndrome via Cloud-Based MRI Images 5. Critical Investigation and Prototype Study on Deep Brain Stimulations: An Application of Biomedical Engineering in Healthcare 6. Insight into Various Algorithms for Medical Image Analyzes Using Convolutional Neural Networks (Deep Learning) 7. Exploration of Deep RNN Architectures: LSTM and GRU in Medical Diagnostics of Cardiovascular and Neuro Diseases 8. Medical Image Classification and Manifold Disease Identification Through Convolutional Neural Networks: A Research Perspective 9. Melanoma Detection on Skin Lesion Images Using K-Means Algorithm and SVM Classifier 10. Role of Deep Learning Techniques in Detecting Skin Cancer: A Review 11. Deep Learning and Its Applications in Biomedical Image Processing