The Bioimaging and Signals track is geared towards students with interests in any of the following areas:
1. Development and application of imaging devices;
2. Signal and image processing methods;
3. Biological/biomedical signal acquisition and analysis;
4. Computational modeling of biomedical signals and systems;
5. Biological/biomedical control systems; and/or
6. Biologically inspired signal and image processing.
This track may be particularly attractive to students with undergraduate degrees in bioengineering/biomedical engineering; electrical engineering; computer science and engineering; math; and/or physics, but it is open to all bioengineering graduate students.
Students who have not had “signals and systems” and/or “linear systems” courses at the undergraduate level, similar to BIOENG 1320, ECE 1552 or MEMS 1014 offered at Pitt, may find that they lack the prerequisites for many of the track courses. Moreover, knowledge of the fundamentals of signals and systems provided in these courses will be required to pass the Preliminary Exam in the Bioimaging and Signals Track. Accordingly, students lacking this background are strongly encouraged to audit or take one of these three courses prior to taking the prelim exam in the late Spring of the 1 st year. (Note that undergraduate courses do not fulfill graduate degree requirements.)
Students in the Bioimaging and Signals Track must complete 9 credits (3 different graduate level courses) in order to satisfy track requirements. At least one of these courses must be in the “bio-imaging” area, and at least one must be in the “signals and systems” area, as follows:
Signals and systems course requirements (choose at least one):
BIOENG 2005 - RADIOFREQUENCY MEDICAL DEVICES AND APPLICATIONS OF ELECTROMAGNETICS IN MEDICINE
ECE 2523 - DIGITAL SIGNAL PROCESSING
ECE 2646 - LINEAR SYSTEM THEORY
Bioimaging course requirements (choose at least one):
BIOENG 2330 - BIOMEDICAL IMAGING
BIOENG 2505 - MULTI MODAL BIOMEDICAL IMAGING TECHNOLOGIES: FUNCTIONAL, MOLECULAR AND HYBRID IMAGING TECHNIQUES
The third track course may be selected from the lists above, or from the list below of the variety of bioimaging and signals courses available through Pitt and CMU that fulfill track requirements. However, the list is by no means comprehensive, and students are free and encouraged to explore course offerings from other science and engineering departments, at Pitt and CMU, including Electrical and Computer Engineering; Computer Science; Physics; and Neuroscience. Coupled with two additional open electives, the track requirements provide flexibility for students, in consultation with their research mentor, to design an appropriate curriculum of graduate study to complement their research.
Possible courses for the 3rd required track course:
Note: courses not listed here require pre-approval by the Track Coordinators in order to fulfill track requirements:
BIOENG 2005 - RADIOFREQUENCY MEDICAL DEVICES AND APPLICATIONS OF ELECTROMAGNETICS IN MEDICINE
BIOENG 2045 - COMPUTATIONAL CASE STUDIES IN BIOMEDICAL ENGINEERING
BIOENG 2186 - NEURAL ENGINEERING
BIOENG 2330 - BIOMEDICAL IMAGING
BIOENG 2383 - BIOMEDICAL OPTICAL MICROSCOPY
BIOENG 2505 - MULTI MODAL BIOMEDICAL IMAGING TECHNOLOGIES: FUNCTIONAL, MOLECULAR AND HYBRID IMAGING TECHNIQUES
BIOENG 2515 - CARDIO SYSTM DYNAMICS & MODELING
ECE 2372 - PATTERN RECOGNITION
ECE 2521 - ANALYSIS STOCHASTIC PROCESSES
ECE 2523 - DIGITAL SIGNAL PROCESSING
ECE 2646 - LINEAR SYSTEM THEORY
ECE 2647 - INTRODUCTION TO NONLINEAR CONTROL DESIGN
ECE 2654 - DIGITAL CONTROL SYSTEMS
ECE 2671 - OPTIMIZATION METHODS
ECE 3374 - APPLICATIONS OF WAVELET TRANSFORMS
ECE 3524 - DIGITAL SPEECH PROCESSING
ECE 3526 - MODERN SPECTRAL ESTIMATION
ECE 3528 - TIME-FREQUENCY SIGNAL ANALYSIS
ECE 3557 - STATISTICAL SIGNAL PROCESSING
ECE 3650 - OPTIMAL CONTROL
MATH 3375 - COMPUTATIONAL NEUROSCIENCE METHODS (can be used as one track course OR fulfill BioE Math requirement)
CMU 10-601 - MACHINE LEARNING
CMU 15-883 - COMPUTATIONAL MODELS OF NEURAL SYSTEMS
CMU 18-660 - NUMERICAL METHODS FOR ENGINEERING DESIGN AND OPTIMIZATION
CMU 18-697 - STATISTICAL DISCOVERY AND LEARNING
CMU 18-698 / 42-590 - NEURAL SIGNAL PROCESSING
CMU 18-781 - SPEECH RECOGNITION AND UNDERSTANDING
CMU 18-790 - WAVELETS AND MULTIRESOLUTION TECHNIQUES
CMU 8-792 - ADVANCED DIGITAL SIGNAL PROCESSING
CMU 36-746 - STATISTICAL METHODS FOR NEUROSCIENCE (CAN BE USED AS A TRACK COURSE OR FULFILL THE BIOE STAT REQUIREMENT)
CMU 86-595 / 42-595 - NEURAL DATA ANALYSIS
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