Machine Learning in Medical Imaging and Computer Vision

BOOKS - Machine Learning in Medical Imaging and Computer Vision

Machine Learning in Medical Imaging and Computer Vision - Amita Nandal, Liang Zhou, Arvind Dhaka, Todor Ganchev 2024 PDF The Institution of Engineering and Technology BOOKS

ECO~15 kg CO²

1 TON

91041

Machine Learning in Medical Imaging and Computer Vision

Author: Amita Nandal, Liang Zhou, Arvind Dhaka, Todor Ganchev
Year: 2024
Pages: 382
Format: PDF
File size: 21.1 MB
Language: ENG

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The book "Machine Learning in Medical Imaging and Computer Vision" provides an overview of the current state of machine learning techniques in medical imaging and computer vision, highlighting their potential applications and challenges. The book covers topics such as image segmentation, object recognition, and image classification, as well as deep learning methods for image analysis and processing. It also discusses the limitations and potential risks associated with these technologies, including issues related to data privacy and security. The book concludes by emphasizing the importance of understanding the technological process of developing modern knowledge as the basis for the survival of humanity and the unity of people in a warring state. The plot of the book revolves around the need to study and understand the process of technology evolution, particularly in the field of machine learning, to ensure the survival of humanity and the unity of people in a warring state. The author argues that the rapid pace of technological advancement has created a sense of urgency to develop a personal paradigm for perceiving the technological process of developing modern knowledge. This paradigm should be based on the principles of simplicity, clarity, and accessibility, allowing individuals to comprehend and adapt to new technologies without feeling overwhelmed or disconnected from society. The book begins by introducing the reader to the basics of machine learning and its applications in medical imaging and computer vision. It explains how machine learning algorithms can be used to analyze and interpret large amounts of data, including images, and how they have revolutionized these fields.

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