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 www.cvip.uofl.edu

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 www.cvip.uofl.edu

Computer Vision Image Processing Laboratory Example of X-ray Imaging Computer Vision Image Processing Laboratory www.cvip.uofl.edu

Computer Vision Image Processing Laboratory Example of X-ray Imaging Computer Vision Image Processing Laboratory www.cvip.uofl.edu

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 www.cvip.uofl.edu

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

Computer Vision Image Processing Laboratory Example of CT Computer Vision Image Processing Laboratory www.cvip.uofl.edu

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 www.cvip.uofl.edu

Computer Vision Image Processing Laboratory Example of MRI Computer Vision Image Processing Laboratory www.cvip.uofl.edu

Computer Vision Image Processing Laboratory 4. Ultrasound Imaging Advantage Real Time Imaging No harmful effect Computer Vision Image Processing Laboratory www.cvip.uofl.edu

Computer Vision Image Processing Laboratory Example of Ultrasound Imaging Computer Vision Image Processing Laboratory www.cvip.uofl.edu

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 www.cvip.uofl.edu

Computer Vision Image Processing Laboratory System Design Preprocessing Data Such as you can filter your images in order to reduce the noise LPF 2. HPF 3. BPF 3. Median filter 4. Gaussian Filter Computer Vision Image Processing Laboratory www.cvip.uofl.edu

Computer Vision Image Processing Laboratory Image 3 x 3 pixel Computer Vision Image Processing Laboratory www.cvip.uofl.edu

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 www.cvip.uofl.edu

Computer Vision Image Processing Laboratory Background Chest Lung Computer Vision Image Processing Laboratory www.cvip.uofl.edu

Computer Vision Image Processing Laboratory How To estimate the Initial Mean for Lung and Chest? Computer Vision Image Processing Laboratory www.cvip.uofl.edu

CT Slice Contain Abnormal Tissues Computer Vision Image Processing Laboratory www.cvip.uofl.edu

Computer Vision Image Processing Laboratory Slice_No. 32 Slice_No. 33 Abnormal tissues Computer Vision Image Processing Laboratory www.cvip.uofl.edu

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 www.cvip.uofl.edu

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 www.cvip.uofl.edu

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 www.cvip.uofl.edu

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 www.cvip.uofl.edu

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 www.cvip.uofl.edu

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 www.cvip.uofl.edu

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 www.cvip.uofl.edu

Computer Vision Image Processing Laboratory This Figure shows the abnormal tissues in the 3-D Computer Vision Image Processing Laboratory www.cvip.uofl.edu

Computer Vision Image Processing Laboratory More Results Computer Vision Image Processing Laboratory www.cvip.uofl.edu