Lung nodule detection and diagnosis using circle detection through plain radiographs
In this paper, we present a system that locates pulmonary nodules in digital chest radiographs through pattern recognition. Digital radiographs that are already diagnosed with lung nodules underwent histogram equalization in order to address varying illumination levels across different regions in th...
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oai:animorepository.dlsu.edu.ph:faculty_research-62772022-04-21T00:38:13Z Lung nodule detection and diagnosis using circle detection through plain radiographs De La Cruz, Ria Rodette Roque, Trizia Roby Ann Rosas, John Daryl Vera Cruz, Charles Vincent M. Cordel, Macario O., II Ilao, Joel P. In this paper, we present a system that locates pulmonary nodules in digital chest radiographs through pattern recognition. Digital radiographs that are already diagnosed with lung nodules underwent histogram equalization in order to address varying illumination levels across different regions in the radiographs, and make the radiograph samples more comparable. Laplacian of Gaussian filtering is next applied in order to highlight the edges of pathological features like nodule-shaped blobs in each radiograph. Circular Hough Transform (CHT) was utilized in tandem with pixel-based image processing techniques in locating possible nodules. These system reports the count and sizes of the candidate nodules. We report an overall system accuracy of 73.33% when classifying digitized radiographs as either with nodules or without nodules. 2013-03-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/5441 Faculty Research Work Animo Repository Pattern recognition systems Image processing—Digital techniques Radiography, Medical—Digital techniques Lungs—Radiography Lungs—Diseases—Diagnosis |
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Pattern recognition systems Image processing—Digital techniques Radiography, Medical—Digital techniques Lungs—Radiography Lungs—Diseases—Diagnosis |
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Pattern recognition systems Image processing—Digital techniques Radiography, Medical—Digital techniques Lungs—Radiography Lungs—Diseases—Diagnosis De La Cruz, Ria Rodette Roque, Trizia Roby Ann Rosas, John Daryl Vera Cruz, Charles Vincent M. Cordel, Macario O., II Ilao, Joel P. Lung nodule detection and diagnosis using circle detection through plain radiographs |
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In this paper, we present a system that locates pulmonary nodules in digital chest radiographs through pattern recognition. Digital radiographs that are already diagnosed with lung nodules underwent histogram equalization in order to address varying illumination levels across different regions in the radiographs, and make the radiograph samples more comparable. Laplacian of Gaussian filtering is next applied in order to highlight the edges of pathological features like nodule-shaped blobs in each radiograph. Circular Hough Transform (CHT) was utilized in tandem with pixel-based image processing techniques in locating possible nodules. These system reports the count and sizes of the candidate nodules. We report an overall system accuracy of 73.33% when classifying digitized radiographs as either with nodules or without nodules. |
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text |
author |
De La Cruz, Ria Rodette Roque, Trizia Roby Ann Rosas, John Daryl Vera Cruz, Charles Vincent M. Cordel, Macario O., II Ilao, Joel P. |
author_facet |
De La Cruz, Ria Rodette Roque, Trizia Roby Ann Rosas, John Daryl Vera Cruz, Charles Vincent M. Cordel, Macario O., II Ilao, Joel P. |
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De La Cruz, Ria Rodette |
title |
Lung nodule detection and diagnosis using circle detection through plain radiographs |
title_short |
Lung nodule detection and diagnosis using circle detection through plain radiographs |
title_full |
Lung nodule detection and diagnosis using circle detection through plain radiographs |
title_fullStr |
Lung nodule detection and diagnosis using circle detection through plain radiographs |
title_full_unstemmed |
Lung nodule detection and diagnosis using circle detection through plain radiographs |
title_sort |
lung nodule detection and diagnosis using circle detection through plain radiographs |
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Animo Repository |
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2013 |
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https://animorepository.dlsu.edu.ph/faculty_research/5441 |
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