Medical Image Analysis
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1 Medical Imaging, SS-2014 Dr. Mohammad Dawood Medical Image Analysis Dr. Mohammad Dawood Department of Computer Science University of Münster Germany
description
Medical Image Analysis. Dr. Mohammad Dawood Department of Computer Science University of Münster Germany. Recap. Grayscale transformations Linear Logarithmic Power law Point operations Local operators Histogram Equalization Adpative /Local Hist Eq Color space Fourier transform - PowerPoint PPT Presentation
Transcript of Medical Image Analysis
Medical Image Analysis
Dr. Mohammad Dawood
Department of Computer Science
University of MünsterGermany
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Medical Imaging, SS-2014
Dr. Mohammad Dawood
Recap
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Medical Imaging, SS-2014
Dr. Mohammad Dawood
Grayscale transformations1. Linear2. Logarithmic3. Power law
Point operations
Local operators
4. Histogram Equalization5. Adpative/Local Hist Eq6. Color space7. Fourier transform8. Spatial filtering
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Medical Imaging, SS-2014
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Edge detection
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Medical Imaging, SS-2014
Dr. Mohammad Dawood
What is an “edge”?Discontinuity in Image brightness
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Recognizing the edge
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Increasing edge thickness- easier to detect and better connected edges
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Strengthening the edges
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Medical Imaging, SS-2014
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Edge detection with spatial operators
Prewitt operators
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Medical Imaging, SS-2014
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Adding operators
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Medical Imaging, SS-2014
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Derivatives of an image
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Magnitude of gradient:
Angle:
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Medical Imaging, SS-2014
Dr. Mohammad Dawood
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First derivative
Forward difference
Backward difference
Central difference
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MRI Spine fw bw cd bw_i bw+bw_i
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Medical Imaging, SS-2014
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Laplace operator
H+V Laplace
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Medical Imaging, SS-2014
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Cardiac PET
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Gaussian+Gradient
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Medical Imaging, SS-2014
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Sobel operators
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Edge detection with spatial operators
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Medical Imaging, SS-2014
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Medical Imaging, SS-2014
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Scharr operators
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Edge detection with spatial operators
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Medical Imaging, SS-2014
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Edge detection with spatial operators
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Medical Imaging, SS-2014
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Canny operator
1. Gaussian for noise reduction
2. Calculation of edges (sobel operator)
3. Non-maximum suppression, no neighbor should have a higher gradient except in the same direction
0 : if intensity > the intensities in the N and S directions45 : if intensity > the intensities in the NW and SE directions90 : if intensity > the intensities in the W and E directions135 : if intensity > the intensities in the NE and SW directions
4. Hysteresisdelete edges below threshold 1keep edges above threshold 2keep edges between thresholds, if one neighbor is above threshold 2
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Medical Imaging, SS-2014
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Canny operator th=0.5 th=0.1
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Medical Imaging, SS-2014
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Marr-Hildreth operator
Laplacian of the Gaussian (LoG)
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Medical Imaging, SS-2014
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Marr Hildreth operator sigma=1 sigma=2
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Medical Imaging, SS-2014
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Hough Transform
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Medical Imaging, SS-2014
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Hough transform for detecting lines
A line can be defined as:
Take the edge map of the image I
Look for the neighbors of a pixel and determine m and b
Accumulate the m and b in an accumulator array
Find the maxima of the accumulator array
Transform them back to image space
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Medical Imaging, SS-2014
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Hough transform for detecting lines
Alternative definition of lines
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Medical Imaging, SS-2014
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Hough transform
Similar transforms can be defined for circles, ellipses or other parametric curves
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Medical Imaging, SS-2014
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Morphological operations
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Medical Imaging, SS-2014
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Morphological operators
Operations are based on Set Theory and require a structure element
Basic morphological operations are:1. Erosion2. Dilation3. Opening4. Closing
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Medical Imaging, SS-2014
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Erosion
If A is an image and B is a structure element then
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Medical Imaging, SS-2014
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Dilation
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Closing
Dilation + Erosion
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Medical Imaging, SS-2014
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Opening
Erosion + Dilation
