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Video Lectures on "Introduction to Biomedical Signal Analysis" by Prof. Jiri Jan

Lecture Videos :

 Introduction to Biomedical Signal Analysis

by Prof. Jiri Jan

Click on Computer () image to view the lecture

W Welcome
 1 Introduction to Selected Concepts
Overview of the lectures (No voice in this lecture)
Part I: Images as Multidimensional Signals
Analogue (Continuous) Images
     Images as Signals
     Some 2D Elementary Signals
     Harmonic 2D Signals
2D systems – Description in the Original Domain
 2      Classification of 2D systems
     2D Linear Systems
     Physical Interpretation of the Superposition Integral
2D Fourier Transform
     Definition of the Forward Transform
     Definition of the 2D Inverse Transform
 3      Physical Interpretation of the 2D FT
     Basic Properties of the 2D FT
2D Systems – Description in the Frequency Domain
     Stochastic Images
 4 Digital Image Representation
     Grey-Scale Histogram
     Reconstruction of Continuous Images from Samples
Discrete 2D Operators
     Discrete 2D Linear Operators
     Separable Linear Operators
 5      Local Operators
     Convolution Operators
     Nonlinear Operators
     Order Statistics Operators
 6 Part III: Reconstruction of Images from Tomographic Projections
Representation of an Image by Projection
     Radon Transform
Algebraic Methods of Reconstruction
     Principle of the Iterative Solution of the Equations
 7 Reconstruction via Frequency Domain
     Reconstruction Based on the Slice Theorem
Filtered Back Projection
 8      Steps of the FBP Reconstruction in Discrete Environment
Reconstruction from Fan Projections
     Geometry of Measurement
     Conversation into Parallel Projections
     Weighted and Filtered Back Projection
 9 Part II: Image Enhancement
Contrast Transforms
     Piecewise Linear Contrast Transform
     Histogram Equalization
10      Pseudo-Coloring
Image Sharpening and Edge Enhancement
     Difference Approximations of Derivatives in Discrete Environment
     Approximations of Isotropic Operators
     Sharpening Operators
     Sharpening via Frequency Domain
     Adaptive Sharpening
11 Noise Suppression
     Classification of Noise
     Suppression of Narrow-Band Noise
     Suppression of Wideband "Grey" Noise
     "Smart" Smoothing
     Suppression of impulse Noise
     Detection of False Pixels
     Suppression of Impulse Noise by Median Filtering

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