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QED and the Men Who Made It
In the 1930s, physics was in a crisis. There appeared to be no way to reconcile the new theory of quantum mechanics with Einstein's theory of relativity. Several approaches had been tried and had failed. In the post-World War II period, four eminent physicists rose to the challenge and developed a calculable version of quantum electrodynamics (QED), probably the most successful theory in physics. This formulation of QED was pioneered by Freeman Dyson, Richard Feynman, Julian Schwinger, and Sin-Itiro Tomonaga, three of whom won the Nobel Prize for their work. In this book, physicist and historian Silvan Schweber tells the story of these four physicists, blending discussions of their scientifi...
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...
Thermodynamics of Membrane Receptors and Channels
Thermodynamics of Membrane Receptors and Channels synthesizes a wealth of new information regarding the biophysics of membrane proteins. New insights provided by molecular genetics, single channel recording, and high resolution structural techniques are discussed from a conceptual perspective. Basic theoretical topics are introduced, developed, and then extensively illustrated with recent results from the literature or data from the authors' own laboratories. Theoretical and experimental information is incorporated into in-depth discussions of ion permeation mechanisms, ion channel and receptor conformational changes, aggregate activity of complexes of lipids and proteins, and how coupling is achieved between different energy modes in the many transduction systems residing in biomembranes. Thermodynamics of Membrane Receptors and Channels will be valuable both as a learning aid and a reference for biophysicists, neuroscientists, cell biologists, physiologists, and other researchers investigating any aspects of biomembranes.
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 ...
LBL Research Review
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Fighting for Love in the Century of Extinction
A call for political action to save the natural world
3D Ultrasound
3D ultrasound techniques have been increasingly used in diagnosis, minimally invasive image-guided interventions, and intra-operative surgical use. Today, most ultrasound system manufacturers provide 3D imaging capability as part of the systems. This availability has stimulated researchers to develop various machine learning tools to automatically detect and diagnose diseases, such as cancer, monitor the progression and regression of diseases, such as carotid atherosclerosis, guide and track tools being introduced into the body, such as brachytherapy and biopsy needles. This edited book is divided into three sections covering 3D ultrasound devices, 3D ultrasound applications, and machine learning tools using 3D ultrasound imaging and written with physicians, engineers, and advanced graduate students in mind. Features: 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
Directory of Research in Physics/astronomy at Primarily Undergraduate Institutions
To increase faculty participation and to recognize the strategic educational position held by undergraduate research, scholarship, and creative activities (URSCA) in many institutions, faculty mentorship of undergraduate students needs to be valued as a standard component of workload and formally included in activity reports and evaluations, including those that lead to reappointment, tenure, and promotion. This white paper presents the need for recognition of faculty mentorship of URSCA, recommends best practices for institutions to adopt, offers a selection of case studies where some of these practices are already established, and summarizes the challenges ahead.
