EE C261. Medical Imaging Signals and Systems

Catalog Description: Biomedical imaging is a clinically important application of engineering, applied mathematics, physics, and medicine. In this course, we apply linear systems theory and basic physics to analyze X-ray imaging, computerized tomography, nuclear medicine, and MRI. We cover the basic physics and instrumentation that characterizes medical image as an ideal perfect-resolution image blurred by an impulse response. This material could prepare the student for a career in designing new medical imaging systems that reliably detect small tumors or infarcts.

Units: 4.0

Course Objectives: • understand how 2D impulse response or 2D spatial frequency transfer function (or Modulation Transfer Function) allow one to quantify the spatial resolution of an imaging system. • understand 2D sampling requirements to avoid aliasing • understand 2D filtered backprojection reconstruction from projections based on the projection-slice theorem of Fourier Transforms • understand the concept of image reconstruction as solving a mathematical inverse problem. • understand the limitations of poorly conditioned inverse problems and noise amplification • understand how diffraction can limit resolution---but not for the imaging systems in this class • understand the hardware components of an X-ray imaging scanner •, • understand the physics and hardware limits to spatial resolution of an X-ray imaging system • understand tradeoffs between depth, contrast, and dose for X-ray sources • understand resolution limits for CT scanners • understand how to reconstruct a 2D CT image from projection data using the filtered backprojection algorithm • understand the hardware and physics of Nuclear Medicine scanners • understand how PET and SPECT images are created using filtered backprojection • understand resolution limits of nuclear medicine scanners • understand MRI hardware components, resolution limits and image reconstruction via a 2D FFT • understand how to construct a medical imaging scanner that will achieve a desired spatial resolution specification.

Student Learning Outcomes: • students will be tested for their understanding of the key concepts above • undergraduate students will apply to graduate programs and be admitted • students will apply this knowledge to their research at Berkeley, UCSF, the national labs or elsewhere • students will be hired by companies that create, sell, operate or consult in biomedical imaging

Prerequisites: El Eng 20N and Engineering 7 or equivalent. Knowledge of Matlab or linear algebra assumed.

Fall: 3.0 hours of lecture and 1.0 hours of discussion per week
Spring: 3.0 hours of lecture and 1.0 hours of discussion per week

Grading basis: letter

Final exam status: Written final exam conducted during the scheduled final exam period

Also listed as: BIO ENG C261, EL ENG C261

Class Schedule (Fall 2019):
TuTh 2:00PM - 3:29PM, Barrows 20 – Steven Michael Conolly

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