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Artificial Intelligence and Image Processing in Medical Imaging: Developments in Biomedical Engineering and Bioelectronics

Editat de Walid A. Zgallai, Dilber Uzun Ozsahin
en Limba Engleză Paperback – 16 ian 2024
Artificial Intelligence and Image Processing in Medical Imaging deals with the applications of processing medical images with a view of improving the quality of the data in order to facilitate better decision- making. The book covers the basics of medical imaging and the fundamentals of image processing. It explains spatial and frequency domain applications of image processing, introduces image compression techniques and their applications, and covers image segmentation techniques and their applications. The book includes object detection and classification applications and provides an overall background to statistical analysis in biomedical systems.
The role of Machine Learning, including Neural Networks, Deep Learning, and the implications of the expansion of artificial intelligence is also covered. With contributions from prominent researchers worldwide, this book provides up-to-date and comprehensive coverage of AI applications in image processing where readers will find the latest information with clear examples and illustrations.


  • Provides the latest comprehensive coverage of the developments of AI techniques and the principles of medical imaging
  • Covers all aspects of medical imaging, from acquisition, the use of hardware and software, image analysis and implementation of AI in problem solving
  • Provides examples of medical imaging and how they’re processed, including segmentation, classification, and detection
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Specificații

ISBN-13: 9780323954624
ISBN-10: 0323954626
Pagini: 436
Dimensiuni: 191 x 235 mm
Greutate: 0.45 kg
Editura: ELSEVIER SCIENCE
Seria Developments in Biomedical Engineering and Bioelectronics


Public țintă

Researchers and biomedical engineers, Postgraduate Fellows, postgraduate and undergraduate Biomedical Engineering students

Cuprins

1. Medical imaging types and acquisition2. Noise, filtering, and artefact rejection3. Frequency domain analysis4. Detection and Classification5. Statistical analysis and characterization6. Pattern recognition, and morphological features7. Introduction to Machine learning and artificial intelligence8. Convolutional neural networks and deep learning9. CT scan AI applications10. MRI AI applications