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3D CT Image Data Visualize Whole lung tissues Using VTK 8 mm

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Presentation on theme: "3D CT Image Data Visualize Whole lung tissues Using VTK 8 mm"— Presentation transcript:

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

3 Computer Vision Image Processing Laboratory
Example of X-ray Imaging Computer Vision Image Processing Laboratory

4 Computer Vision Image Processing Laboratory
Example of X-ray Imaging Computer Vision Image Processing Laboratory

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 Computer Vision Image Processing Laboratory

6 Computer Vision Image Processing Laboratory
Disadvantage 1. Ct has harmful effect due to radiation dose (X-ray) Computer Vision Image Processing Laboratory

7 Computer Vision Image Processing Laboratory
Example of CT Computer Vision Image Processing Laboratory

8 Computer Vision Image Processing Laboratory
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

9 Computer Vision Image Processing Laboratory
Example of MRI Computer Vision Image Processing Laboratory

10 Computer Vision Image Processing Laboratory
4. Ultrasound Imaging Advantage Real Time Imaging No harmful effect Computer Vision Image Processing Laboratory

11 Computer Vision Image Processing Laboratory
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 Computer Vision Image Processing Laboratory

14 Computer Vision Image Processing Laboratory
Image 3 x 3 pixel Computer Vision Image Processing Laboratory

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 Computer Vision Image Processing Laboratory

16 Computer Vision Image Processing Laboratory
Background Chest Lung Computer Vision Image Processing Laboratory

17 Computer Vision Image Processing Laboratory
How To estimate the Initial Mean for Lung and Chest? Computer Vision Image Processing Laboratory

18 CT Slice Contain Abnormal Tissues
Computer Vision Image Processing Laboratory

19 Computer Vision Image Processing Laboratory
Slice_No. 32 Slice_No. 33 Abnormal tissues Computer Vision Image Processing Laboratory

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) Computer Vision Image Processing Laboratory

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 Computer Vision Image Processing Laboratory

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 Computer Vision Image Processing Laboratory

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 Computer Vision Image Processing Laboratory

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 Computer Vision Image Processing Laboratory

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 Computer Vision Image Processing Laboratory

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 Computer Vision Image Processing Laboratory

27 Computer Vision Image Processing Laboratory
This Figure shows the abnormal tissues in the 3-D Computer Vision Image Processing Laboratory

28 Computer Vision Image Processing Laboratory
More Results Computer Vision Image Processing Laboratory


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