printer friendly pageRAD 211: Biomedical Signals I (BMP 211)
This course builds the foundational skills for analyzing biomedical signals and systems. Students will learn about biomedical signal processing (with emphasis on two-dimensional signals), linear systems and their properties, the Fourier transform and its applications, spatial/time domain vs frequency domain, and sampling theory. Examples will be drawn from medical imaging modalities such as MR, x-ray, CT, and ultrasound to demonstrate linear systems analysis and medical image reconstruction using Fourier transform methods.
Terms: Aut
| Units: 3
RAD 212: Biomedical Signals II (BMP 212)
This course examines the stochastic nature of biomedical signals and systems and introduces concepts from statistical signal processing to characterize and account for noise in signals and images. Students will learn about random variables, random processes, estimation theory, and image quality. Examples will be drawn from medical imaging modalities such as x-ray, CT, ultrasound, and MR to demonstrate how noise can be modeled and how information is extracted from noisy signals.
Last offered: Winter 2023
RAD 220: Introduction to Imaging and Image-based Human Anatomy (BIOE 220, BMP 220)
Focus on learning the fundamentals of each imaging modality including X-ray Imaging, Ultrasound, CT, and MRI, to learn normal human anatomy and how it appears on medical images, to learn the relative strengths of the modalities, and to answer, "What am I looking at?" Course website:
http://bioe220.stanford.edu
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 222: Physics and Engineering Principles of Multi-modality Molecular Imaging of Living Subjects (BIOE 222, BMP 222)
Physics and Engineering Principles of Multi-modality Molecular Imaging of Living Subjects (
RAD 222A). Focuses on instruments, algorithms and other technologies for non-invasive imaging of molecular processes in living subjects. Introduces research and clinical molecular imaging modalities, including PET, SPECT, MRI, Ultrasound, Optics, and Photoacoustics. For each modality, lectures cover the basics of the origin and properties of imaging signal generation, instrumentation physics and engineering of signal detection, signal processing, image reconstruction, image data quantification, applications of machine learning, and applications of molecular imaging in medicine and biology research.
Terms: Aut
| Units: 3-4
Instructors:
Levin, C. (PI)
RAD 223: Physics and Engineering of X-Ray Computed Tomography (BIOE 223)
CT scanning geometries, production of x-rays, interactions of x-rays with matter, 2D and 3D CT reconstruction, image presentation, image quality performance parameters, system components, image artirfacts, radiation dose. Prerequisites: differential and integral calculus. Knowledge of Fourier transforms (
EE261) recommended.
Last offered: Autumn 2016
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 225: Transcranial Ultrasound Neuromodulation: Physics, Neurophysiology, and Applications (BIOE 225, BMP 225)
This course covers the basic concepts of ultrasound neuromodulation, including basic neurophysiology, ultrasound physics and applications, and comparison to other neuromodulation modalities. The physics component will include acoustic properties of biological tissues, transducer hardware, beam formation, and beam modeling. Lectures on applications will include ultrasonic manipulation of behavior with therapeutic implications.Comparisons will be made to other neuromodulation modalities including DBS and TMS. We will include guest appearances from world-class experts in the field. Lectures will be online for asynchronous viewing. In-class components will include hands-on laboratories to demonstrate the techniques described in lecture and discussions with ourselves and the external speakers. Course website:
http://bioe225.stanford.edu.
Last offered: Autumn 2021
RAD 226: MRI Spin Physics, Relaxation Theory, and Contrast Mechanisms (BIOE 226, BMP 226)
This course covers fundamental principles of magnetic resonance imaging (MRI) and spectroscopy (MRS) focusing on the analytic tools needed to understand interactions among nuclear spins, relaxation processes, and image contrast. Starting from a quantum mechanical description of NMR, we'll study J-coupling, the most mathematically tractable coupling mechanism, and its fundamental importance in MRS. Next, we will extend these concepts to develop NMR relaxation theory, which provides the foundation for analyzing multiple in vivo MRI contrast mechanisms and contrast agents..
Last offered: Spring 2023
RAD 227: Functional MRI Methods (BIOE 227, BIOPHYS 227, BMP 227)
Basics of functional magnetic resonance neuroimaging, including data acquisition, analysis, and experimental design. Journal club sections. Cognitive neuroscience and clinical applications. Prerequisites: basic physics, mathematics; neuroscience recommended.
Last offered: Spring 2023
Filter Results: