computer vision image processing laboratory detection, visualization, and identification of lung...
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Computer Vision Image Processing Laboratory
www.cvip.uofl.edu
Detection, Visualization, and Identification of Lung Abnormalities in Chest Spiral CT Scans
Abnormality
Detection System
Removing Background
Making stochastic Model using Gibbs
Markov Random Field
Apply ICM using Genetic and EM
algorithm
Visualize Whole lung tissues Using VTK
Visualize Abnormal Tissues Using VTK
3D CT Image Data
8 mm
Registration
Computer Vision Image Processing Laboratory
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Medical ImagingTypes of medical Imaging
1. X-ray ImagingAdvantage Cheap
Disadvantage
It is just a projection of an object
Computer Vision Image Processing Laboratory
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Example of X-ray Imaging
Computer Vision Image Processing Laboratory
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Example of X-ray Imaging
Computer Vision Image Processing Laboratory
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2. computed tomography (CT) Advantage
1. better Geometry of the scanned subject
2. Using CT we can build 3-D model of the scanned subject
3. Give high contrast between bones and soft tissues
Computer Vision Image Processing Laboratory
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Disadvantage
1. Ct has harmful effect due to radiation dose (X-ray)
Computer Vision Image Processing Laboratory
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Example of CT
Computer Vision Image Processing Laboratory
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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
Computer Vision Image Processing Laboratory
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Example of MRI
Computer Vision Image Processing Laboratory
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4. Ultrasound Imaging
Advantage
1. Real Time Imaging
2. No harmful effect
Computer Vision Image Processing Laboratory
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Example of Ultrasound Imaging
Computer Vision Image Processing Laboratory
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Abnormality Detection System
Removing Background
Making stochastic Model using Gibbs
Markov Random Field
Apply ICM using Genetic and EM
algorithm
Visualize Whole lung tissues Using VTK
Visualize Abnormal Tissues Using VTK
3D CT Image Data
8 mm
Registration
Automated Lung Abnormality Detection System
Computer Vision Image Processing Laboratory
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System Design
1. Preprocessing Data
Such as you can filter your images in order to reduce the noise
1. LPF 2. HPF 3. BPF
3. Median filter 4. Gaussian Filter
Computer Vision Image Processing Laboratory
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Image 3 x 3 pixel
Computer Vision Image Processing Laboratory
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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 Image after removing background
Original Image 3x3 pixels
Image 3 x 3 pixels after
applying the algorithm
Computer Vision Image Processing Laboratory
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LungChest
Background
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How To estimate the Initial Mean for Lung and Chest?
Computer Vision Image Processing Laboratory
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CT Slice Contain Abnormal Tissues
Abnormal tissues
Computer Vision Image Processing Laboratory
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Abnormal tissues
Slice_No. 32
Slice_No. 33
Computer Vision Image Processing Laboratory
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Abnormality Detection Criteria
Each Ring Shape will take three ranks
1. Radial uniformity (R)
2. Position of the ring shape relative to the center of right or left lung edge (P)
3. Connectivity between different slices (C)
Computer Vision Image Processing Laboratory
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Remove the Normal Tissues
Detecting
ring shape
Compute The Total Rank (R) for Each
ring shapeR> 2
Abnormal
Tissues
Normal
Tissues
yes
No
Abnormality System detection
Computer Vision Image Processing Laboratory
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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 After Removing normal
Tissues Histogram of the CT
slice
Computer Vision Image Processing Laboratory
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c. Ranking
1. NR, measures the uniformity distribution of the edges.
2. NC, measures the connectivity that the pixel (x, y) appears in
the same location in different slices
3. 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
Computer Vision Image Processing Laboratory
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4. Results
(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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(f) Bronchi, bronchioles and abnormal tissues
(g) Abnormal tissues detected by our algorithm
(h) Manual detection by expert doctor
Computer Vision Image Processing Laboratory
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Building 3-D modelWe 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
Computer Vision Image Processing Laboratory
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This Figure shows the abnormal tissues in the 3-D
Computer Vision Image Processing Laboratory
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More Results