Digital Edge Detection Based Pneumonia Detection in Chest Radiographs
In response to the demand of pneumonia diagnosis, a digital detection algorithm utilizing chest X-ray images has been proposed. Despite this, X-ray images have the tendency of noise and spatial aliasing that tend to cause blurring of some boundaries, thus the importance of having a better edge detec...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2024-01-01
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| Series: | ITM Web of Conferences |
| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2024/11/itmconf_icaetm2024_01014.pdf |
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| author | Poola Rahul Gowtham Kommineni Prema Teja Lahari P.L Yellampalli Siva Sankar |
| author_facet | Poola Rahul Gowtham Kommineni Prema Teja Lahari P.L Yellampalli Siva Sankar |
| author_sort | Poola Rahul Gowtham |
| collection | DOAJ |
| description | In response to the demand of pneumonia diagnosis, a digital detection algorithm utilizing chest X-ray images has been proposed. Despite this, X-ray images have the tendency of noise and spatial aliasing that tend to cause blurring of some boundaries, thus the importance of having a better edge detection algorithm is more warranted. The article presents a SIMULINK-based model for the process of edge detection, testing the performance of Canny, Laplacian of Gaussian, Prewitt, Sobel and Robert algorithms and most importantly their simulated results. Since some of the X rays are suspected to be afflicted by pneumonia, the radiographs are also converted into string numbers based on the features extracted as the Xray’s area of interest. One of the basic processes in image processing is the quality assessment of images, this work advocates for the inclusion of the objective criteria for the evaluation of the segmented images. Some performance evaluation metrics for various edge detection models are given and the relationships showed that the bacterial pneumonia affliction X rays have feature string values under 100 whereas the nonbacterial pneumonia X rays have values above 100. |
| format | Article |
| id | doaj-art-dab90cc3bf884944affaa80f01b338d0 |
| institution | Kabale University |
| issn | 2271-2097 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | ITM Web of Conferences |
| spelling | doaj-art-dab90cc3bf884944affaa80f01b338d02024-12-13T10:03:56ZengEDP SciencesITM Web of Conferences2271-20972024-01-01680101410.1051/itmconf/20246801014itmconf_icaetm2024_01014Digital Edge Detection Based Pneumonia Detection in Chest RadiographsPoola Rahul Gowtham0Kommineni Prema Teja1Lahari P.L2Yellampalli Siva Sankar3Department of Electronics and Communication Engineering, SRM UniversityDepartment of Electronics and Communication Engineering, SRM UniversityDepartment of Electronics and Communication Engineering, SRM UniversityDepartment of Electronics and Communication Engineering, SRM UniversityIn response to the demand of pneumonia diagnosis, a digital detection algorithm utilizing chest X-ray images has been proposed. Despite this, X-ray images have the tendency of noise and spatial aliasing that tend to cause blurring of some boundaries, thus the importance of having a better edge detection algorithm is more warranted. The article presents a SIMULINK-based model for the process of edge detection, testing the performance of Canny, Laplacian of Gaussian, Prewitt, Sobel and Robert algorithms and most importantly their simulated results. Since some of the X rays are suspected to be afflicted by pneumonia, the radiographs are also converted into string numbers based on the features extracted as the Xray’s area of interest. One of the basic processes in image processing is the quality assessment of images, this work advocates for the inclusion of the objective criteria for the evaluation of the segmented images. Some performance evaluation metrics for various edge detection models are given and the relationships showed that the bacterial pneumonia affliction X rays have feature string values under 100 whereas the nonbacterial pneumonia X rays have values above 100.https://www.itm-conferences.org/articles/itmconf/pdf/2024/11/itmconf_icaetm2024_01014.pdf |
| spellingShingle | Poola Rahul Gowtham Kommineni Prema Teja Lahari P.L Yellampalli Siva Sankar Digital Edge Detection Based Pneumonia Detection in Chest Radiographs ITM Web of Conferences |
| title | Digital Edge Detection Based Pneumonia Detection in Chest Radiographs |
| title_full | Digital Edge Detection Based Pneumonia Detection in Chest Radiographs |
| title_fullStr | Digital Edge Detection Based Pneumonia Detection in Chest Radiographs |
| title_full_unstemmed | Digital Edge Detection Based Pneumonia Detection in Chest Radiographs |
| title_short | Digital Edge Detection Based Pneumonia Detection in Chest Radiographs |
| title_sort | digital edge detection based pneumonia detection in chest radiographs |
| url | https://www.itm-conferences.org/articles/itmconf/pdf/2024/11/itmconf_icaetm2024_01014.pdf |
| work_keys_str_mv | AT poolarahulgowtham digitaledgedetectionbasedpneumoniadetectioninchestradiographs AT komminenipremateja digitaledgedetectionbasedpneumoniadetectioninchestradiographs AT laharipl digitaledgedetectionbasedpneumoniadetectioninchestradiographs AT yellampallisivasankar digitaledgedetectionbasedpneumoniadetectioninchestradiographs |