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Candidate Tree-In-Bud Pattern Selection and Classification Using Ball Scale Encoding Algorithm


Affiliations
1 Department of Computer Science and Engineering, Mepco Schlenk Engineering College, India
2 Department of Information Technology, Kamaraj College of Engineering and Technology, India
     

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Asthma, Chronic obstructive pulmonary disease, influenza, pneumonia, tuberculosis, lung cancer and many other breathing problems are the leading causes of death and disability all over the world. These diseases affect the lung. Radiology is a primary assessing method with low specificity of the prediction of the presence of these diseases. Computer Assisted Detection (CAD) will help the specialists in detecting one of these diseases in an early stage. A method has been proposed by Ulas Bagci to detect lung abnormalities using Fuzzy connected object estimation, Ball scale encoding and comparing various features extracted from local patches of the lung images (CT scan). In this paper, the Tree-in-Bud patterns are selected after segmentation by using ball scale encoding algorithm.

Keywords

Computer Assisted Detection, Tree in Bud Opacities, Fuzzy Connectedness, Ball Scale encoding, Wilmore Energy Features, Support Vector Machine.
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  • Candidate Tree-In-Bud Pattern Selection and Classification Using Ball Scale Encoding Algorithm

Abstract Views: 189  |  PDF Views: 0

Authors

T. Akilandeswari
Department of Computer Science and Engineering, Mepco Schlenk Engineering College, India
N. Balaganesh
Department of Computer Science and Engineering, Mepco Schlenk Engineering College, India
S. RadhaKrishnan
Department of Information Technology, Kamaraj College of Engineering and Technology, India

Abstract


Asthma, Chronic obstructive pulmonary disease, influenza, pneumonia, tuberculosis, lung cancer and many other breathing problems are the leading causes of death and disability all over the world. These diseases affect the lung. Radiology is a primary assessing method with low specificity of the prediction of the presence of these diseases. Computer Assisted Detection (CAD) will help the specialists in detecting one of these diseases in an early stage. A method has been proposed by Ulas Bagci to detect lung abnormalities using Fuzzy connected object estimation, Ball scale encoding and comparing various features extracted from local patches of the lung images (CT scan). In this paper, the Tree-in-Bud patterns are selected after segmentation by using ball scale encoding algorithm.

Keywords


Computer Assisted Detection, Tree in Bud Opacities, Fuzzy Connectedness, Ball Scale encoding, Wilmore Energy Features, Support Vector Machine.