A modified Tseng algorithm approach to restoring thoracic diseases' computerized tomography images
It is well-known that the Tseng algorithm and its modifications have been successfully employed in approximating zeros of the sum of monotone operators. In this study, we restored various thoracic diseases' computerized tomography (CT) images, which were degraded with a known blur function and...
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| Veröffentlicht in: | PloS one 2024-07, Vol.19 (7), p.e0305728 |
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| description | It is well-known that the Tseng algorithm and its modifications have been successfully employed in approximating zeros of the sum of monotone operators. In this study, we restored various thoracic diseases' computerized tomography (CT) images, which were degraded with a known blur function and additive noise, using a modified Tseng algorithm. The test images used in the study depict calcification of the Aorta, Subcutaneous Emphysema, Tortuous Aorta, Pneumomediastinum, and Pneumoperitoneum. Additionally, we employed well-known image restoration tools to enhance image quality and compared the quality of restored images with the originals. Finally, the study demonstrates the potential to advance monotone inclusion problem-solving, particularly in the field of medical image recovery. |
| doi_str_mv | 10.1371/journal.pone.0305728 |
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In this study, we restored various thoracic diseases' computerized tomography (CT) images, which were degraded with a known blur function and additive noise, using a modified Tseng algorithm. The test images used in the study depict calcification of the Aorta, Subcutaneous Emphysema, Tortuous Aorta, Pneumomediastinum, and Pneumoperitoneum. Additionally, we employed well-known image restoration tools to enhance image quality and compared the quality of restored images with the originals. Finally, the study demonstrates the potential to advance monotone inclusion problem-solving, particularly in the field of medical image recovery.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0305728</identifier><identifier>PMID: 39046956</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Aorta ; Biology and Life Sciences ; Calcification ; Computed tomography ; Coronary vessels ; CT imaging ; Disease ; Diseases ; Emphysema ; Humans ; Image enhancement ; Image quality ; Image restoration ; Magnetic resonance imaging ; Mathematical models ; Medical diagnosis ; Medical imaging ; Medical imaging equipment ; Medical research ; Medicine and Health Sciences ; Medicine, Experimental ; Noise ; Physical Sciences ; Pneumonia ; Problem solving ; Regularization methods ; Research and Analysis Methods ; Thoracic Diseases - diagnostic imaging ; Thorax ; Tomography ; Tomography, X-Ray Computed - methods ; X-rays</subject><ispartof>PloS one, 2024-07, Vol.19 (7), p.e0305728</ispartof><rights>Copyright: © 2024 Ozsahin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2024 Public Library of Science</rights><rights>2024 Ozsahin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 Ozsahin et al 2024 Ozsahin et al</rights><rights>2024 Ozsahin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c572t-f848f40368ce8a3335e5f5b2b836482fefdb2ac350a7a204ae499362a12aa6113</cites><orcidid>0000-0003-2508-9710</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11268622/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11268622/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39046956$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ozsahin, Dilber Uzun</creatorcontrib><creatorcontrib>Adamu, Abubakar</creatorcontrib><creatorcontrib>Aliyu, Maryam Rabiu</creatorcontrib><creatorcontrib>Umar, Huzaifa</creatorcontrib><title>A modified Tseng algorithm approach to restoring thoracic diseases' computerized tomography images</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>It is well-known that the Tseng algorithm and its modifications have been successfully employed in approximating zeros of the sum of monotone operators. In this study, we restored various thoracic diseases' computerized tomography (CT) images, which were degraded with a known blur function and additive noise, using a modified Tseng algorithm. The test images used in the study depict calcification of the Aorta, Subcutaneous Emphysema, Tortuous Aorta, Pneumomediastinum, and Pneumoperitoneum. Additionally, we employed well-known image restoration tools to enhance image quality and compared the quality of restored images with the originals. 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In this study, we restored various thoracic diseases' computerized tomography (CT) images, which were degraded with a known blur function and additive noise, using a modified Tseng algorithm. The test images used in the study depict calcification of the Aorta, Subcutaneous Emphysema, Tortuous Aorta, Pneumomediastinum, and Pneumoperitoneum. Additionally, we employed well-known image restoration tools to enhance image quality and compared the quality of restored images with the originals. Finally, the study demonstrates the potential to advance monotone inclusion problem-solving, particularly in the field of medical image recovery.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>39046956</pmid><doi>10.1371/journal.pone.0305728</doi><tpages>e0305728</tpages><orcidid>https://orcid.org/0000-0003-2508-9710</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Algorithms Aorta Biology and Life Sciences Calcification Computed tomography Coronary vessels CT imaging Disease Diseases Emphysema Humans Image enhancement Image quality Image restoration Magnetic resonance imaging Mathematical models Medical diagnosis Medical imaging Medical imaging equipment Medical research Medicine and Health Sciences Medicine, Experimental Noise Physical Sciences Pneumonia Problem solving Regularization methods Research and Analysis Methods Thoracic Diseases - diagnostic imaging Thorax Tomography Tomography, X-Ray Computed - methods X-rays |
| title | A modified Tseng algorithm approach to restoring thoracic diseases' computerized tomography images |
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