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1 - 10 of 22 results for: RAD

RAD 101: Readings in Radiology Research

Prerequisite: consent of instructor.
Terms: Aut, Win, Spr, Sum | Units: 1-18 | Repeatable for credit
Instructors: Atlas, S. (PI) ; Bammer, R. (PI) ; Barnes, P. (PI) ; Barth, R. (PI) ; Bazalova, M. (PI) ; Beaulieu, C. (PI) ; Becker, C. (PI) ; Biswal, S. (PI) ; Blankenberg, F. (PI) ; Chan, F. (PI) ; Cheng, Z. (PI) ; Chin, F. (PI) ; Dahl, J. (PI) ; Daldrup-Link, H. (PI) ; Daniel, B. (PI) ; Demirci, U. (PI) ; Desser, T. (PI) ; Do, H. (PI) ; Fahrig, R. (PI) ; Federle, M. (PI) ; Fischbein, N. (PI) ; Fleischmann, D. (PI) ; Gayer, G. (PI) ; Ghanouni, P. (PI) ; Glover, G. (PI) ; Gold, G. (PI) ; Goris, M. (PI) ; Hargreaves, B. (PI) ; Herfkens, R. (PI) ; Hofmann, L. (PI) ; Hovsepian, D. (PI) ; Hwang, G. (PI) ; Iagaru, A. (PI) ; Ikeda, D. (PI) ; Jaramillo, D. (PI) ; Jeffrey, R. (PI) ; KUO, W. (PI) ; Kamaya, A. (PI) ; Kane, P. (PI) ; Kao, J. (PI) ; Keeling, C. (PI) ; Kothary, N. (PI) ; Lachman, R. (PI) ; Langlotz, C. (PI) ; Larson, D. (PI) ; Lebowitz, E. (PI) ; Leung, A. (PI) ; Levin, C. (PI) ; Lipson, J. (PI) ; Loening, A. (PI) ; Louie, J. (PI) ; Lungren, M. (PI) ; Lutz, A. (PI) ; Mallick, P. (PI) ; Marks, M. (PI) ; Massoud, T. (PI) ; McNab, J. (PI) ; Moseley, M. (PI) ; Moskowitz, P. (PI) ; Napel, S. (PI) ; Newman, B. (PI) ; Nino-Murcia, M. (PI) ; Olcott, E. (PI) ; Paik, D. (PI) ; Pal, S. (PI) ; Paulmurugan, R. (PI) ; Pauly, K. (PI) ; Pelc, N. (PI) ; Pitteri, S. (PI) ; Plevritis, S. (PI) ; Quon, A. (PI) ; Rao, J. (PI) ; Riley, G. (PI) ; Rubesova, E. (PI) ; Rubin, D. (PI) ; Rutt, B. (PI) ; Segall, G. (PI) ; Seidel, F. (PI) ; Shin, L. (PI) ; Soh, H. (PI) ; Spielman, D. (PI) ; Stevens, K. (PI) ; Stoyanova, T. (PI) ; Sze, D. (PI) ; Thakor, A. (PI) ; Van Dalsem, V. (PI) ; Vasanawala, S. (PI) ; Wintermark, M. (PI) ; Yao, D. (PI) ; Yeom, K. (PI) ; Zaharchuk, G. (PI) ; Zeineh, M. (PI)

RAD 189: Career Building: Entrepreneurship / Intrapreneurship, People, Innovation, Decision-Making and Impact (CHEMENG 189, CHEMENG 289, ENGR 289, RAD 289)

This course is designed to enable graduate students and advanced undergraduate students in science and engineering to hone strategies for career success. Drawing strongly on entrepreneurial principles and lessons from industry, the course complements the traditional curriculum by focusing on career-building tools that students need to improve their professional prospects and achieve their goals. Relevant for those who plan to pursue careers in academia and industry alike, a central focus will be on managing one's career as if it were a start-up, emphasizing principles that empower individuals to take more control of their futures: investing in yourself, building professional networks, taking intelligent risks, and making uncertainty and volatility work to one's advantage. Through a series of in-classroom presentations and interviews - with professors, entrepreneurs, executives, athletes, investors, and thought leaders from diverse fields and sectors - students will gain important knowledge and practical strategies, with course modules on topics such as ideation and innovation, the skill of self-advocacy, the fundamentals of negotiation, building and managing teams, and effective communication and storytelling. Additional modules will focus on biotechnology and deep tech start-up companies, as well as strategies for cultivating a successful academic career. The idea for this course emerged from the instructor's reflections on 30 years of research, teaching, mentorship, and deep entrepreneurial experiences spanning the gamut of approaches to translational science - academic discovery, invention, conceiving of and leading multi-institutional research centers, building research and business teams, launching and financing start-ups, building business models to advance real-world applications of cutting-edge science, and seeing through research-based companies to success (including growing an idea into a multi-billion dollar company). For this course, students will be expected to complete relevant reading assignments, participate actively in class dialogue, and complete regular writing assignments focused on course topics as they relate to ones own career-building needs and professional aspirations. Students may also have opportunities to lead class discussions on topics of interest.
Terms: Win | Units: 3

RAD 199: Undergraduate Research

Students undertake investigations sponsored by individual faculty members. Prerequisite: consent of instructor.
Terms: Aut, Win, Spr, Sum | Units: 1-18 | Repeatable for credit
Instructors: Airan, R. (PI) ; Bammer, R. (PI) ; Barnes, P. (PI) ; Barth, R. (PI) ; Beaulieu, C. (PI) ; Becker, C. (PI) ; Biswal, S. (PI) ; Blankenberg, F. (PI) ; Chan, F. (PI) ; Chaudhari, A. (PI) ; Cheng, Z. (PI) ; Chin, F. (PI) ; Dahl, J. (PI) ; Daldrup-Link, H. (PI) ; Daniel, B. (PI) ; Demirci, U. (PI) ; Desser, T. (PI) ; Do, H. (PI) ; Durmus, G. (PI) ; Ennis, D. (PI) ; Federle, M. (PI) ; Ferrara, K. (PI) ; Fischbein, N. (PI) ; Fleischmann, D. (PI) ; Gayer, G. (PI) ; Ghanouni, P. (PI) ; Glover, G. (PI) ; Gold, G. (PI) ; Goris, M. (PI) ; Hargreaves, B. (PI) ; Herfkens, R. (PI) ; Hofmann, L. (PI) ; Hovsepian, D. (PI) ; Hwang, G. (PI) ; Iagaru, A. (PI) ; Ikeda, D. (PI) ; Jaramillo, D. (PI) ; Jeffrey, R. (PI) ; KUO, W. (PI) ; Kamaya, A. (PI) ; Kane, P. (PI) ; Kao, J. (PI) ; Keeling, C. (PI) ; Kothary, N. (PI) ; Lachman, R. (PI) ; Langlotz, C. (PI) ; Larson, D. (PI) ; Lebowitz, E. (PI) ; Leung, A. (PI) ; Levin, C. (PI) ; Lipson, J. (PI) ; Loening, A. (PI) ; Louie, J. (PI) ; Lungren, M. (PI) ; Lutz, A. (PI) ; Mallick, P. (PI) ; Marks, M. (PI) ; Massoud, T. (PI) ; McNab, J. (PI) ; Moseley, M. (PI) ; Moskowitz, P. (PI) ; Napel, S. (PI) ; Newman, B. (PI) ; Nino-Murcia, M. (PI) ; Olcott, E. (PI) ; Paik, D. (PI) ; Pal, S. (PI) ; Paredes Castro, P. (PI) ; Paulmurugan, R. (PI) ; Pauly, K. (PI) ; Pelc, N. (PI) ; Pitteri, S. (PI) ; Plevritis, S. (PI) ; Popelka, G. (PI) ; Quon, A. (PI) ; Rao, J. (PI) ; Riley, G. (PI) ; Rubesova, E. (PI) ; Rubin, D. (PI) ; Rusu, M. (PI) ; Rutt, B. (PI) ; Segall, G. (PI) ; Seidel, F. (PI) ; Shin, L. (PI) ; Soh, H. (PI) ; Spielman, D. (PI) ; Stevens, K. (PI) ; Stoyanova, T. (PI) ; Sze, D. (PI) ; Thakor, A. (PI) ; Van Dalsem, V. (PI) ; Vasanawala, S. (PI) ; Wang, A. (PI) ; Wintermark, M. (PI) ; Wu, J. (PI) ; Yao, D. (PI) ; Yeom, K. (PI) ; Zaharchuk, G. (PI) ; Zeineh, M. (PI)

RAD 220: Introduction to Imaging and Image-based Human Anatomy (BIOE 220, BMP 220)

Terms: Win | Units: 3

RAD 221: Physics and Engineering of Radionuclide-based Medical Imaging (BIOE 221, BMP 221)

Physics, instrumentation, and algorithms for radionuclide-based medical imaging, with a focus on positron emission tomography (PET) and single photon emission computed tomography (SPECT). Topics include basic physics of photon emission from the body and detection, sensors, readout and data acquisition electronics, system design, strategies for tomographic image reconstruction, system calibration and data correction algorithms, methods of image quantification, and image quality assessment, and current developments in the field. Prerequisites: A year of university-level mathematics and physics.
Terms: Win | Units: 3

RAD 224: Probes and Applications for Multi-modality Molecular Imaging of Living Subjects (BIOE 224, BMP 224)

We will focus on design, development, and application of imaging agents that target specific cellular and molecular aspects of disease. Covers the strengths and limitations of different imaging agents and how to optimize their design for image-guided intra-operative procedures, brain imaging, probing infection, or interrogating tumor metabolism. Emphasis this year will be on clinical molecular imaging, state-of-the-art strategies for early detection of dementia, imaging response to cancer immunotherapy, and how 'Deep Learning' can be used for probe design and high-throughput automated image analysis.
Terms: Win | Units: 3 | Repeatable 2 times (up to 8 units total)

RAD 235: Advanced Ultrasound Imaging (BMP 235)

The focus of this course is on advanced ultrasound imaging techniques for medical imaging applications. Topics include beamforming, adaptive beamforming, Fourier beamforming, synthetic aperture techniques, speckle, speckle reduction, k-space, harmonic imaging, coherence imaging, phase aberration, radiation force imaging, elastography, quantitative ultrasound, Doppler and flow imaging, ultrasounds modeling and advanced ultrasound theory.
Terms: Win | Units: 3

RAD 271: Foundation Models for Healthcare (BIODS 271, CS 277)

Generative AI and large-scale self-supervised foundation models are poised to have a profound impact on human decision making across occupations. Healthcare is one such area where such models have the capacity to impact patients, clinicians, and other care providers. In this course, we will explore the training, evaluation, and deployment of generative AI and foundation models, with a focus on addressing current and future medical needs. The course will cover models used in natural language processing, computer vision, and multi-modal applications. We will explore the intersection of models trained on non-healthcare domains and their adaptation to domain-specific problems, as well as healthcare-specific foundation models. Prerequisites: Familiarity with machine learning principles at the level of CS 229, 231N, or 224N
Terms: Win | Units: 3

RAD 280: Early Clinical Experience in Radiology

Provides an observational experience as determined by the instructor and student. Prerequisite: consent of instructor.
Terms: Aut, Win, Spr, Sum | Units: 1-2 | Repeatable for credit
Instructors: Atlas, S. (PI) ; Bammer, R. (PI) ; Barnes, P. (PI) ; Barth, R. (PI) ; Bazalova, M. (PI) ; Beaulieu, C. (PI) ; Becker, C. (PI) ; Biswal, S. (PI) ; Blankenberg, F. (PI) ; Chan, F. (PI) ; Cheng, Z. (PI) ; Chin, F. (PI) ; Dahl, J. (PI) ; Daldrup-Link, H. (PI) ; Daniel, B. (PI) ; Demirci, U. (PI) ; Desser, T. (PI) ; Do, H. (PI) ; Fahrig, R. (PI) ; Federle, M. (PI) ; Fischbein, N. (PI) ; Fleischmann, D. (PI) ; Gayer, G. (PI) ; Ghanouni, P. (PI) ; Glover, G. (PI) ; Gold, G. (PI) ; Goris, M. (PI) ; Hargreaves, B. (PI) ; Herfkens, R. (PI) ; Hofmann, L. (PI) ; Hovsepian, D. (PI) ; Hwang, G. (PI) ; Iagaru, A. (PI) ; Ikeda, D. (PI) ; Jaramillo, D. (PI) ; Jeffrey, R. (PI) ; KUO, W. (PI) ; Kamaya, A. (PI) ; Kane, P. (PI) ; Kao, J. (PI) ; Keeling, C. (PI) ; Kothary, N. (PI) ; Lachman, R. (PI) ; Langlotz, C. (PI) ; Larson, D. (PI) ; Lebowitz, E. (PI) ; Leung, A. (PI) ; Levin, C. (PI) ; Lipson, J. (PI) ; Loening, A. (PI) ; Louie, J. (PI) ; Lungren, M. (PI) ; Lutz, A. (PI) ; Mallick, P. (PI) ; Marks, M. (PI) ; Massoud, T. (PI) ; McNab, J. (PI) ; Mittra, E. (PI) ; Moseley, M. (PI) ; Moskowitz, P. (PI) ; Napel, S. (PI) ; Newman, B. (PI) ; Nino-Murcia, M. (PI) ; Olcott, E. (PI) ; Paik, D. (PI) ; Pal, S. (PI) ; Paulmurugan, R. (PI) ; Pauly, K. (PI) ; Pelc, N. (PI) ; Pitteri, S. (PI) ; Plevritis, S. (PI) ; Quon, A. (PI) ; Rao, J. (PI) ; Riley, G. (PI) ; Rubesova, E. (PI) ; Rubin, D. (PI) ; Rutt, B. (PI) ; Segall, G. (PI) ; Seidel, F. (PI) ; Shin, L. (PI) ; Soh, H. (PI) ; Spielman, D. (PI) ; Stevens, K. (PI) ; Stoyanova, T. (PI) ; Sze, D. (PI) ; Thakor, A. (PI) ; Van Dalsem, V. (PI) ; Vasanawala, S. (PI) ; Wintermark, M. (PI) ; Wu, J. (PI) ; Yao, D. (PI) ; Yeom, K. (PI) ; Zaharchuk, G. (PI) ; Zeineh, M. (PI)

RAD 289: Career Building: Entrepreneurship / Intrapreneurship, People, Innovation, Decision-Making and Impact (CHEMENG 189, CHEMENG 289, ENGR 289, RAD 189)

This course is designed to enable graduate students and advanced undergraduate students in science and engineering to hone strategies for career success. Drawing strongly on entrepreneurial principles and lessons from industry, the course complements the traditional curriculum by focusing on career-building tools that students need to improve their professional prospects and achieve their goals. Relevant for those who plan to pursue careers in academia and industry alike, a central focus will be on managing one's career as if it were a start-up, emphasizing principles that empower individuals to take more control of their futures: investing in yourself, building professional networks, taking intelligent risks, and making uncertainty and volatility work to one's advantage. Through a series of in-classroom presentations and interviews - with professors, entrepreneurs, executives, athletes, investors, and thought leaders from diverse fields and sectors - students will gain important knowledge and practical strategies, with course modules on topics such as ideation and innovation, the skill of self-advocacy, the fundamentals of negotiation, building and managing teams, and effective communication and storytelling. Additional modules will focus on biotechnology and deep tech start-up companies, as well as strategies for cultivating a successful academic career. The idea for this course emerged from the instructor's reflections on 30 years of research, teaching, mentorship, and deep entrepreneurial experiences spanning the gamut of approaches to translational science - academic discovery, invention, conceiving of and leading multi-institutional research centers, building research and business teams, launching and financing start-ups, building business models to advance real-world applications of cutting-edge science, and seeing through research-based companies to success (including growing an idea into a multi-billion dollar company). For this course, students will be expected to complete relevant reading assignments, participate actively in class dialogue, and complete regular writing assignments focused on course topics as they relate to ones own career-building needs and professional aspirations. Students may also have opportunities to lead class discussions on topics of interest.
Terms: Win | Units: 3
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