Automated Lung Cancer Segmentation in Tissue Micro Array Analysis Histopathological Images Using a Prototype of Computer-Assisted Diagnosis
Lung cancer is a fatal disease that kills approximately 85% of those diagnosed with it. In recent years, advances in medical imaging have greatly improved the acquisition, storage, and visualization of various pathologies, making it a necessary component in medicine today. Develop a computer-aided d...
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| Published in: | Journal of personalized medicine Vol. 13; no. 3; p. 388 |
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| Abstract | Lung cancer is a fatal disease that kills approximately 85% of those diagnosed with it. In recent years, advances in medical imaging have greatly improved the acquisition, storage, and visualization of various pathologies, making it a necessary component in medicine today.
Develop a computer-aided diagnostic system to detect lung cancer early by segmenting tumor and non-tumor tissue on Tissue Micro Array Analysis (TMA) histopathological images.
The prototype computer-aided diagnostic system was developed to segment tumor areas, non-tumor areas, and fundus on TMA histopathological images.
The system achieved an average accuracy of 83.4% and an F-measurement of 84.4% in segmenting tumor and non-tumor tissue.
The computer-aided diagnostic system provides a second diagnostic opinion to specialists, allowing for more precise diagnoses and more appropriate treatments for lung cancer. |
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| AbstractList | BACKGROUNDLung cancer is a fatal disease that kills approximately 85% of those diagnosed with it. In recent years, advances in medical imaging have greatly improved the acquisition, storage, and visualization of various pathologies, making it a necessary component in medicine today. OBJECTIVEDevelop a computer-aided diagnostic system to detect lung cancer early by segmenting tumor and non-tumor tissue on Tissue Micro Array Analysis (TMA) histopathological images. METHODThe prototype computer-aided diagnostic system was developed to segment tumor areas, non-tumor areas, and fundus on TMA histopathological images. RESULTSThe system achieved an average accuracy of 83.4% and an F-measurement of 84.4% in segmenting tumor and non-tumor tissue. CONCLUSIONThe computer-aided diagnostic system provides a second diagnostic opinion to specialists, allowing for more precise diagnoses and more appropriate treatments for lung cancer. Background: Lung cancer is a fatal disease that kills approximately 85% of those diagnosed with it. In recent years, advances in medical imaging have greatly improved the acquisition, storage, and visualization of various pathologies, making it a necessary component in medicine today. Objective: Develop a computer-aided diagnostic system to detect lung cancer early by segmenting tumor and non-tumor tissue on Tissue Micro Array Analysis (TMA) histopathological images. Method: The prototype computer-aided diagnostic system was developed to segment tumor areas, non-tumor areas, and fundus on TMA histopathological images. Results: The system achieved an average accuracy of 83.4% and an F-measurement of 84.4% in segmenting tumor and non-tumor tissue. Conclusion: The computer-aided diagnostic system provides a second diagnostic opinion to specialists, allowing for more precise diagnoses and more appropriate treatments for lung cancer. Lung cancer is a fatal disease that kills approximately 85% of those diagnosed with it. In recent years, advances in medical imaging have greatly improved the acquisition, storage, and visualization of various pathologies, making it a necessary component in medicine today. Develop a computer-aided diagnostic system to detect lung cancer early by segmenting tumor and non-tumor tissue on Tissue Micro Array Analysis (TMA) histopathological images. The prototype computer-aided diagnostic system was developed to segment tumor areas, non-tumor areas, and fundus on TMA histopathological images. The system achieved an average accuracy of 83.4% and an F-measurement of 84.4% in segmenting tumor and non-tumor tissue. The computer-aided diagnostic system provides a second diagnostic opinion to specialists, allowing for more precise diagnoses and more appropriate treatments for lung cancer. |
| Audience | Academic |
| Author | Abdulrahman, Elsadig Eltaher Hamed Alotaibi, Faisal Fahad Osman, Abdalla Mohamed Ahmed Abdalla, Yahya Hussein Ahmed Alhemairy, Maram Abdulkhalek Althubaity, DaifAllah D Alwesabi, Sadeq Abdo Al-Khadher, Mugahed Ali |
| AuthorAffiliation | 2 Strategy Studies and Planning Department, Prince Sultan Medical Military City, Riyadh 13521, Saudi Arabia 3 Community and Mental Health, College of Nursing, Najran University, Najran 66441, Saudi Arabia 1 Pediatric Nursing Department, Faculty of Nursing, Najran University, Najran 66441, Saudi Arabia 4 Nursing College, Najran University, Najran 66441, Saudi Arabia |
| AuthorAffiliation_xml | – name: 3 Community and Mental Health, College of Nursing, Najran University, Najran 66441, Saudi Arabia – name: 4 Nursing College, Najran University, Najran 66441, Saudi Arabia – name: 2 Strategy Studies and Planning Department, Prince Sultan Medical Military City, Riyadh 13521, Saudi Arabia – name: 1 Pediatric Nursing Department, Faculty of Nursing, Najran University, Najran 66441, Saudi Arabia |
| Author_xml | – sequence: 1 givenname: DaifAllah D surname: Althubaity fullname: Althubaity, DaifAllah D organization: Pediatric Nursing Department, Faculty of Nursing, Najran University, Najran 66441, Saudi Arabia – sequence: 2 givenname: Faisal Fahad surname: Alotaibi fullname: Alotaibi, Faisal Fahad organization: Strategy Studies and Planning Department, Prince Sultan Medical Military City, Riyadh 13521, Saudi Arabia – sequence: 3 givenname: Abdalla Mohamed Ahmed surname: Osman fullname: Osman, Abdalla Mohamed Ahmed organization: Community and Mental Health, College of Nursing, Najran University, Najran 66441, Saudi Arabia – sequence: 4 givenname: Mugahed Ali surname: Al-Khadher fullname: Al-Khadher, Mugahed Ali organization: Nursing College, Najran University, Najran 66441, Saudi Arabia – sequence: 5 givenname: Yahya Hussein Ahmed orcidid: 0000-0002-9805-4669 surname: Abdalla fullname: Abdalla, Yahya Hussein Ahmed organization: Nursing College, Najran University, Najran 66441, Saudi Arabia – sequence: 6 givenname: Sadeq Abdo orcidid: 0000-0002-7075-7880 surname: Alwesabi fullname: Alwesabi, Sadeq Abdo organization: Nursing College, Najran University, Najran 66441, Saudi Arabia – sequence: 7 givenname: Elsadig Eltaher Hamed surname: Abdulrahman fullname: Abdulrahman, Elsadig Eltaher Hamed organization: Nursing College, Najran University, Najran 66441, Saudi Arabia – sequence: 8 givenname: Maram Abdulkhalek surname: Alhemairy fullname: Alhemairy, Maram Abdulkhalek organization: Nursing College, Najran University, Najran 66441, Saudi Arabia |
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| Cites_doi | 10.15537/smj.2016.11.16269 10.1016/j.cmpb.2011.12.007 10.1093/bioinformatics/16.10.906 10.1007/s11831-021-09648-w 10.1016/j.semradonc.2007.10.006 10.1155/2013/263190 10.9790/0853-15100494101 10.1007/s10278-019-00295-z 10.2196/16709 10.1016/j.ymeth.2014.06.015 10.1007/s00428-021-03106-5 10.1016/j.compbiomed.2021.104253 10.1021/acs.jcim.9b00662 10.1513/pats.200809-100TH 10.3390/math10050796 10.1038/s41598-018-37638-9 10.3390/jimaging3040061 10.1200/JCO.2008.17.3567 10.1109/RBME.2009.2034865 10.1093/nar/gkm861 10.4103/0971-3026.155831 10.1007/s13193-012-0142-6 10.1016/S0033-3506(02)00023-9 10.1088/1742-6596/841/1/012013 10.1080/21642583.2014.956265 |
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| Snippet | Lung cancer is a fatal disease that kills approximately 85% of those diagnosed with it. In recent years, advances in medical imaging have greatly improved the... Background: Lung cancer is a fatal disease that kills approximately 85% of those diagnosed with it. In recent years, advances in medical imaging have greatly... BACKGROUNDLung cancer is a fatal disease that kills approximately 85% of those diagnosed with it. In recent years, advances in medical imaging have greatly... |
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| SubjectTerms | Automation Biopsy Cancer Datasets Development and progression Diagnosis Disease Histopathology Lung cancer Medical imaging Medical prognosis Precision medicine Software Tumors |
| Title | Automated Lung Cancer Segmentation in Tissue Micro Array Analysis Histopathological Images Using a Prototype of Computer-Assisted Diagnosis |
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