National University of Sciences and Technology
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BMES-821 Signals and Images in Medicine
Campus SMME
Programs PG
Session Spring Semester 2017
Course Title Signals and Images in Medicine
Course Code BMES-821
Credit Hours 3-0
Pre-Requisutes None
Course Objectives Medical signal and image processing is an active area of research. This course presents the fundamentals of digital signal processing with particular emphasis on problems in biomedical research and clinical medicine. It covers principles and algorithms for processing both deterministic and random signals. Topics include data acquisition, imaging, filtering, coding, feature extraction, and modeling. The focus of the course is a series of labs that provide practical experience in processing physiological data, with examples from cardiology, speech processing, and medical imaging. The students shall learn to apply research methods.
Detail Content Biomedical Signals and Images
Introduction to body signals.
ECG: Cardiac electrophysiology, relation of electrocardiogram (ECG) components to cardiac events, clinical applications. EEG and EMG: Basics of EEG, concept of different bands in EEG and EMG.
Imaging Modalities: Survey of major modalities for medical imaging: ultrasound, X-ray, CT, MRI, PET, and SPECT.
MRI: Physics and signal processing for magnetic resonance imaging.
Surgical Applications: A survey of surgical applications of medical image processing.
Fundamentals of Deterministic Signal and Image Processing
Data Acquisition: Sampling in time, aliasing, interpolation, and quantization.
Digital Filtering: Difference equations, FIR and IIR filters, basic properties of discrete-time systems, convolution.
DTFT: The discrete-time Fourier transform and its properties. FIR filter design using windows.
DFT: The discrete Fourier transform and its properties, the fast Fourier transform (FFT), the overlap-save algorithm, digital filtering of continuous-time signals.
Sampling: Sampling and aliasing in time and frequency, spectral analysis.
Image processing I: Extension of filtering and Fourier methods to 2-D signals and systems.
Image processing II: Interpolation, noise reduction methods, edge detection, homomorphic filtering.
Random Signals I: Time averages, ensemble averages, autocorrelation functions, crosscorrelation functions.
Random signals II: Random signals and linear systems, power spectra, cross spectra, Wiener filters.
Blind source separation: Use of principal component analysis (PCA) and independent component analysis (ICA) for filtering.
Image Segmentation and Registration
Image Segmentation: statistical classification, morphological operators, connected components.
Image Registration I: Rigid and non-rigid transformations, objective functions.
Image Registration II: Joint entropy, optimization methods.
Text/Ref Books Gonzales, R. C.: Digital Image Processing, Prentice Hall, New Jersey, 2008.
Eugene N. Bruce, Biomedical Signal Processing and Signal Modeling, John Wiley & Sons,
2000
Geoff Doughetry: Digital Image Processing for Medical Applications
Time Schedule Spring Semester 2017
Faculty/Resource Person Dr M Nabeel Anwar, CEng MIMechE, MIET
PhD (University of Genova) Italy
Discipline: Biomedical Engineering and Sciences
Specialization: Neuroscience, Neuralengineering, EEG signal processing,
Rehabilitation engineering

Dr. Syed Omar Gilani
PhD, NUS, Singapore
Discipline: Biomedical Engineering and Sciences
Specialization: Image Processing