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              <text>Radon transform processed neural network for lung X-ray image based diagnosis</text>
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              <text>neural network; radon transform</text>
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              <text>A novel method for image diagnosis with artificial learning is presented-ray images tuberculosis patients is subjected to neural network learning for prediction of diagnosis. The X-ray images of lungs are normally difficult for diagnosis, since its similarity to lung cancer. Under and over diagnosis of lung X-ray images is a difficult medical problem to resolve. In the present work radon transform of the x-ray images is fed to back propagation neural network trained with Levenberg algorithm. The present methodology gives sharp results, distincting the normal and abnormal images.  2014 IEEE.</text>
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              <text>Sharma C.; Basheer S.; Francis A.; Jayakrishna V.</text>
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              <text>2014 International Conference for Convergence of Technology, I2CT 2014</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>2014-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1109/I2CT.2014.7092284" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/I2CT.2014.7092284&lt;/a&gt;
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              <text>ISBN: 978-147993759-2</text>
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              <text>Sharma C., Department of CSE, Christ University, Bangalore, India; Basheer S., Department of CSE, Amal Jyothi College of Engineering, Kerala, India; Francis A., SENSE, Vellore Institute of Technology, Tamilnadu, India; Jayakrishna V., Department of CSE, Amal Jyothi College of Engineering, Kanjirapally, Kottayam, India</text>
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