1. Detection, Visualization, and Identification of Lung Abnormalities in Chest Spiral CT Scans
3D CT Image Data
Visualize Whole lung tissues Using VTK
8 mm
Making stochastic Model using Gibbs Markov Random Field
Removing Background
Apply ICM using Genetic and EM algorithm
Visualize Abnormal Tissues Using VTK
Abnormality Detection System
Registration
Computer Vision Image Processing Laboratory

2. Computer Vision Image Processing Laboratory
Medical Imaging
Types of medical Imaging
1. X-ray Imaging
Advantage
Cheap
Disadvantage
It is just a projection of an object
Computer Vision Image Processing Laboratory

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Example of X-ray Imaging
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Example of X-ray Imaging
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5. 2. computed tomography (CT)
Advantage
better Geometry of the scanned subject
Using CT we can build 3-D model of the scanned subject
3. Give high contrast between bones and soft tissues
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Disadvantage
1. Ct has harmful effect due to radiation dose (X-ray)
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Example of CT
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3. Magnetic Resonance Imaging (MRI)
Advantage
1. Give high contrast of soft tissues
Disadvantages
1. Does not preserve the geometry of the scanned subject if it is compared with CT
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Example of MRI
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4. Ultrasound Imaging
Advantage
Real Time Imaging
No harmful effect
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Example of Ultrasound Imaging
Computer Vision Image Processing Laboratory

12. Automated Lung Abnormality Detection System
Visualize Whole lung tissues Using VTK
3D CT Image Data
8 mm
Making stochastic Model using Gibbs Markov Random Field
Removing Background
Apply ICM using Genetic and EM algorithm
Visualize Abnormal Tissues Using VTK
Abnormality Detection System
Registration
Computer Vision Image Processing Laboratory

13. Computer Vision Image Processing Laboratory
System Design
Preprocessing Data
Such as you can filter your images in order to reduce the noise
LPF HPF BPF
3. Median filter Gaussian Filter
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Image 3 x 3 pixel
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15. applying the algorithm
1. Remove the background
Starting from the edge of the image, neighboring pixels are compared. Pixels having the same gray levels are removed (I.e., belong to the same region), while those differing are kept.
Original Image 3x3 pixels
Original image Image after removing background
Image 3 x 3 pixels after
applying the algorithm
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Background
Chest
Lung
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How To estimate the Initial Mean for Lung and Chest?
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18. CT Slice Contain Abnormal Tissues
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Slice_No. 32
Slice_No. 33
Abnormal tissues
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20. Abnormality Detection Criteria
Each Ring Shape will take three ranks
Radial uniformity (R)
Position of the ring shape relative to the center of right or left lung edge (P)
Connectivity between different slices (C)
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21. Abnormality System detection
Tissues
yes
Remove the Normal Tissues
Detecting
ring shape
Compute The Total Rank (R) for Each ring shape
R> 2 No
Normal
Tissues
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22. a. Removing the normal tissues
In order to remove the normal tissues of the lung, we will compute the histogram for each slice and search for its peak, and then remove all pixels beneath this peak.
Before Removing normal Tissues
Histogram of the CT slice
After Removing normal Tissues
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23. c. Ranking NR, measures the uniformity distribution of the edges.
NC, measures the connectivity that the pixel (x, y) appears in the same location in different slices
NP, each pixel given a rank NP reflecting its position relative to the center of the right lung or the left lung.
Total Rank (N)= NR + NC + NP
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24. 4. Results Computer Vision Image Processing Laboratory
(a) Original slice from a spiral CT scan of a patient
(b) Slice after removing the background
(c) Desired tissues
(e) The isolated lungs
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25. Computer Vision Image Processing Laboratory www.cvip.uofl.edu
(f) Bronchi, bronchioles and abnormal tissues
(g) Abnormal tissues detected by our algorithm
(h) Manual detection by expert doctor
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26. 3-D model for the whole lung tissues
Building 3-D model
We use VTK tool to build 3-D model for the whole lung tissues and abnormal tissues, bronchi, and bronchioles
3-D model for the whole lung tissues
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This Figure shows the abnormal tissues in the 3-D
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More Results
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