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Introductory Biomedical Imaging
Imaging is everywhere. We use our eyes to see and cameras to take pictures. Scientists use microscopes and telescopes to peer into cells and out to space. Doctors use ultrasound, X-rays, radioisotopes, and MRI to look inside our bodies. If you are curious about imaging, open this textbook to learn the fundamentals. Imaging is a powerful tool in fundamental and applied scientific research and also plays a crucial role in medical diagnostics, treatment, and research. This undergraduate textbook introduces cutting-edge imaging techniques and the physics underlying them. Elementary concepts from electromagnetism, optics, and modern physics are used to explain prominent forms of light microscopy,...
3D Printing in Radiation Oncology
3D Printing in Radiation Oncology: Personalization of Patient Treatment Through Digital Fabrication presents a comprehensive and practical view of the many forms in which 3D printing is being integrated into radiation oncology practice. Radiation oncology employs among the most sophisticated digital technologies in medicine. Until recently, however, the “last mile” of treatment has required manually produced or generic devices for patient set up, positioning, control of surface dose, and delivery of brachytherapy treatment. 3D printing is already offering enhancements in both precision and efficiency through the digital design and fabrication of patient photon and electron bolus, customi...
Artificial Intelligence in Radiation Oncology and Biomedical Physics
This pioneering book explores how machine learning and other AI techniques impact millions of cancer patients who benefit from ionizing radiation. It features contributions from global researchers and clinicians, focusing on the clinical applications of machine learning for medical physics. AI and machine learning have attracted much recent attention and are being increasingly adopted in medicine, with many clinical components and commercial software including aspects of machine learning integration. General principles and important techniques in machine learning are introduced, followed by discussion of clinical applications, particularly in radiomics, outcome prediction, registration and s...
Medical Image Synthesis
Image synthesis across and within medical imaging modalities is an active area of research with broad applications in radiology and radiation oncology. This book covers the principles and methods of medical image synthesis, along with state-of-the-art research. First, various traditional non-learning-based, traditional machine-learning-based, and recent deep-learning-based medical image synthesis methods are reviewed. Second, specific applications of different inter- and intra-modality image synthesis tasks and of synthetic image-aided segmentation and registration are introduced and summarized, listing and highlighting the proposed methods, study designs, and reported performances with the ...
Unsolved Civil Rights Murder Cases, 1934-1970
The Emmett Till Unsolved Civil Rights Crime Act of 2007 called for review and reinvestigation of "violations of criminal civil rights statutes that occurred not later than December 31, 1969, and resulted in a death." The U.S. Attorney General's review observed that date, while examining cases from 1936 (a date not specified in the Till Act) onward. In selecting violations for review, certain "headline" cases were included while others meeting the same criteria were not considered. This first full-length survey of American civil rights "cold cases" examines unsolved racially motivated murders over nearly four decades, beginning in 1934. The author covers all cases reviewed by the federal government to date, as well as a larger number of cases that were ignored without official explanation.
Montgomery Co, TN
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3D Ultrasound
• Provides descriptions of mechanical, tracking, and array approaches for generating 3D ultrasound images • Details the applications of 3D ultrasound for diagnostic application and in image-guided intervention and surgery • Explores the cutting-edge use of machine learning in detection, diagnosis, monitoring, and guidance for a variety of clinical applications
