Real Time Medical Image Processing
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Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing
Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management. Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology. This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems. This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning. FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field
Real-Time Medical Image Processing
Author: Morio Onoe
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
In order to rea1ize real-time medica1 imaging systems, such as are used for computed tomography, automated miscroscopy, dynamic radioisotope imaging, etc., special techno1ogy is required. The high-speed image sour ce must be successfu11y married with the u1tra high-speed computer. Usua11y the ordinary genera1-purpose computer is found to be inadequate to the image generation and/or image pro cessing task. The ordinary computer executes instructions at be tween 1 and 10 million per second. Speed has improved by only about a factor of 10 during the past 20 years. In contrast a typical com puter used in recognizing blood cell images at 10,000 per hour must execute instructions at between 1 billion and 10 billion per second. Simi1ar execution rates are required to construct a computed tomogra phy image in real-time (1 to 10 seconds). For the reasons given above, engineering development in image generation and processing in the field of biomedicine has become a discipline unto itself; a discipline wherein the computer engineer is driven to design extremely high-speed machines that far surpass the ordinary computer and the x-ray, radioisotope, or microscope scanner designer must also produce equipment whose specifications extend far beyond the state-of-the-art."
Biomedical Image Processing
Author: Thomas Martin Deserno
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-03-01
In modern medicine, imaging is the most effective tool for diagnostics, treatment planning and therapy. Almost all modalities have went to directly digital acquisition techniques and processing of this image data have become an important option for health care in future. This book is written by a team of internationally recognized experts from all over the world. It provides a brief but complete overview on medical image processing and analysis highlighting recent advances that have been made in academics. Color figures are used extensively to illustrate the methods and help the reader to understand the complex topics.