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HST.582J/6.555J/16.456J
Lecture Topics
(grouped by topic; see
calendar for order of
presentation)
A. Biomedical Signals and Images
ECG: Cardiac electrophysiology, relation of
electrocardiogram (ECG) components to cardiac events, clinical
applications. Guest lecture.
Speech Signals: The source-filter model of speech production,
spectrographic analysis of speech.
Speech Coding: Analysis-synthesis systems, channel vocoders,
linear prediction of speech, linear prediction vocoders
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. Guest lecture.
Surgical Applications: A survey of surgical applications of
medical image processing. Guest lecture.
B. 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 Revisited: 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.
C. Probability and Random Signals
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.
Hypothesis Testing I: Confidence Intervals, Decision Functions, Receiver Operating Characteristic Curves.
Hypothesis Testing II: Bayes' Rule, Bayes' Classifier, Risk Adjusted Bayes' Classifier.
Estimating PDFs: Practical techniques for estimating PDFs from real
data.
Random Signals III: Kalman filtering.
D. 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.
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