Buch, Englisch, 196 Seiten, Format (B × H): 156 mm x 234 mm
Recent Advances and Future Trends
Buch, Englisch, 196 Seiten, Format (B × H): 156 mm x 234 mm
Reihe: Artificial Intelligence in Smart Healthcare Systems
ISBN: 978-1-03-237992-0
Verlag: Taylor & Francis Ltd
- Delivers an ideal introduction to image processing in medicine, emphasizing the clinical relevance and special requirements of the field
- Presents key principles by implementing algorithms from scratch and using simple MATLAB®/Octave scripts with image data
- Provides an overview of the physics of medical image processing alongside discussing image formats and data storage, intensity transforms, filtering of images and applications of the Fourier transform, three-dimensional spatial transforms, volume rendering, image registration, and tomographic reconstruction
- Highlights the new potential applications of machine learning techniques to the solution of important problems in biomedical image applications
This book is for students, scholars, and professionals of biomedical technology and healthcare data analytics.
Zielgruppe
Postgraduate and Undergraduate Advanced
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
- Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Spiele-Programmierung, Rendering, Animation
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
Weitere Infos & Material
Editor Biographies. List of Contributors. Chapter 1 Journey into the Digital Frontier: Demystifying Neural Networks and Deep Learning. Chapter 2 An In-Depth Analysis of Deep Learning’s Multifaceted Influence on Healthcare Systems. Chapter 3 Monitoring and Diagnosis of Health Using Deep Learning Methods. Chapter 4 A Survey: Recent Advances and Clinical Applications of Deep Learning in Medical Image Analysis. Chapter 5 A Deep Learning Framework to Detect Diabetic Retinopathy Using CNN. Chapter 6 Skin Cancer Detection and Classification Using Deep Learning Techniques. Chapter 7 Prediction of Epidermis Disease Outbreak Using Deep Learning. Chapter 8 Deep Learning-Based Medical Image Segmentation: A Comprehensive Investigation. Chapter 9 Unleashing the Potential of Deep Learning in Diabetic Retinopathy: A Comprehensive Survey. Chapter 10 Enhancing Cardiovascular Health Diagnosis through Predictive Analysis of Electronic Health Records. Index.