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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

Dr. Mohammad Dawood

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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Medical Imaging, SS-2014

Dr. Mohammad Dawood

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Recognizing the edge

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

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Increasing edge thickness- easier to detect and better connected edges

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

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Strengthening the edges

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

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Edge detection with spatial operators

Prewitt operators

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

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Adding operators

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

Derivatives of an image

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Magnitude of gradient:

Angle:

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

-1 1

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

Dr. Mohammad Dawood

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Laplace operator

H+V Laplace

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

Cardiac PET

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

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Gaussian+Gradient

* =

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

Sobel operators

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Edge detection with spatial operators

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

Scharr operators

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Edge detection with spatial operators

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

Roberts operators0 1

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Edge detection with spatial operators

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

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

Dr. Mohammad Dawood

Canny operator th=0.5 th=0.1

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

Marr-Hildreth operator

Laplacian of the Gaussian (LoG)

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

Marr Hildreth operator sigma=1 sigma=2

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

Hough Transform

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

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

Dr. Mohammad Dawood

Hough transform for detecting lines

Alternative definition of lines

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

Hough transform

Similar transforms can be defined for circles, ellipses or other parametric curves

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

Morphological operations

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

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

Dr. Mohammad Dawood

Erosion

If A is an image and B is a structure element then

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X

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

Dilation

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

Closing

Dilation + Erosion

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Medical Imaging, SS-2014

Dr. Mohammad Dawood

Opening

Erosion + Dilation

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