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11 - 20 of 31 results for: BIOE

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

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

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

BIOE 227: Functional MRI Methods (BIOPHYS 227, BMP 227, RAD 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.
Terms: Win | Units: 3

BIOE 261: 3D Bioprinting Laboratory

3D bioprinting promises engineered tissues with precise structure, composition, and cellular architecture. This biofabrication technology lies at the interface of biology, bioengineering, materials science, and instrumentation. This course will teach some of the latest technologies through fundamental lectures and hands-on 3D bioprinting workshops. Student groups will embark on independent projects to innovate in any aspect or application of 3D bioprinting hardware, wetware, or software. Experience in tissue engineering ( BIOE260), instrumentation ( BIOE123), or biomaterials ( MATSCI 381) is helpful but not required.
Terms: Win | Units: 4

BIOE 271: Frugal Science

As a society, we find ourselves surrounded by planetary-scale challenges ranging from lack of equitable access to health care to environmental degradation to dramatic loss of biodiversity. One common theme that runs across these challenges is the need to invent cost-effective solutions with the potential to scale. The COVID-19 pandemic provides yet another example of such a need. In this course, participants will learn principles of frugal science to design scalable solutions with a cost versus performance rubric and explore creative means to break the accessibility barrier. Using historic and current examples, we will emphasize the importance of first-principles science to tackle design challenges with everyday building blocks. Enrollment is open to all Stanford students from all schools/majors, who will team up with collaborators from across the globe to build concrete solutions to planetary-scale challenges. Come learn how to solve serious challenges with a little bit of play.
Terms: Win | Units: 4

BIOE 281: Biomechanics of Movement (ME 281)

Experimental techniques to study human and animal movement including motion capture systems, EMG, force plates, medical imaging, and animation. The mechanical properties of muscle and tendon, and quantitative analysis of musculoskeletal geometry. Projects and demonstrations emphasize applications of mechanics in sports, orthopedics, and rehabilitation.
Terms: Win | Units: 3

BIOE 282: Introduction to Biomechanics and Mechanobiology (ME 283)

Introduction to the mechanical analysis of tissues (biomechanics), and how mechanical cues play a role in regulating tissue development, adaptation, regeneration, and aging (mechanobiology). Topics include tissue viscoelasticity, cardiovascular biomechanics, blood rheology, interstitial flow, bone mechanics, muscle contraction and mechanics, and mechanobiology of the musculoskeletal system. Undergraduates should have taken ME70 and ME80, or equivalent courses.
Terms: Win | Units: 3

BIOE 283: Mechanotransduction in Cells and Tissues (BIOPHYS 244, ME 244)

Mechanical cues play a critical role in development, normal functioning of cells and tissues, and various diseases. This course will cover what is known about cellular mechanotransduction, or the processes by which living cells sense and respond to physical cues such as physiological forces or mechanical properties of the tissue microenvironment. Experimental techniques and current areas of active investigation will be highlighted. This class is for graduate students only.
Terms: Win | Units: 3

BIOE 300A: Molecular and Cellular Bioengineering

Learn some of the fundamental principles and cutting edge research topics in molecular and cellular bioengineering, while improving your scientific communication and quantitative skills. The course is structured around weekly discussions of selected articles, and includes oral presentations, written critiques, and problem sets. Example topics: DNA sequencing, transcriptional regulation, genetic engineering, protein engineering, cell signaling, and synthetic biological circuits. In addition, you will practice computing probabilities, solving differential equations, and coding stochastic simulations (some require Python).
Terms: Win | Units: 3
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