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Tytuł:
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Detection of Pancreatic Cancer in CT Scan Images Using PSO SVM and Image Processing.
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Autorzy:
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Ansari AS; Department of Information Technology, College of Computer and Information Sciences, Majmaah University, Al-Majmaah 11952, Saudi Arabia.
Zamani AS; Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.
Mohammadi MS; Department of Information Technology, College of Computer, Qassim University, Buraydah, Saudi Arabia.
Meenakshi; GD Goenka University Sohna Haryana, India.
Ritonga M; Universitas Muhammadiyah Sumatera Barat, Indonesia.
Ahmed SS; Department of Computer Engineering, Qassim University, Buraydah, Saudi Arabia.
Pounraj D; BVC Engineering College (Autonomous), Odalarevu, Allavaram Mandal, East-GodhavariDistrict, Andhra Pradesh, India.
Kaliyaperumal K; IT @ IoT-HH Campus, Ambo University, Ethiopia.
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Źródło:
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BioMed research international [Biomed Res Int] 2022 Jul 26; Vol. 2022, pp. 8544337. Date of Electronic Publication: 2022 Jul 26 (Print Publication: 2022).
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Typ publikacji:
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Journal Article; Retracted Publication
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Język:
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English
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Imprint Name(s):
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Original Publication: New York, NY : Hindawi Pub. Co.
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MeSH Terms:
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Pancreatic Neoplasms*/diagnostic imaging
Support Vector Machine*
Algorithms ; Bayes Theorem ; Humans ; Image Processing, Computer-Assisted/methods ; Tomography, X-Ray Computed
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References:
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N Engl J Med. 2014 Sep 11;371(11):1039-49. (PMID: 25207767)
IEEE Trans Image Process. 2015 Dec;24(12):5854-67. (PMID: 26462198)
Comput Math Methods Med. 2022 Apr 8;2022:6841334. (PMID: 35432588)
Radiol Imaging Cancer. 2021 Jul;3(4):e210010. (PMID: 34241550)
Pancreatology. 2021 Aug;21(5):1001-1008. (PMID: 33840636)
Pancreas. 2021 Mar 1;50(3):251-279. (PMID: 33835956)
Lancet Digit Health. 2020 Sep;2(9):e453. (PMID: 33328111)
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Entry Date(s):
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Date Created: 20220805 Date Completed: 20220808 Latest Revision: 20240117
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Update Code:
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20240117
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PubMed Central ID:
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PMC9345701
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DOI:
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10.1155/2022/8544337
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PMID:
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35928919
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A diagnosis of pancreatic cancer is one of the worst cancers that may be received anywhere in the world; the five-year survival rate is very less. The majority of cases of this condition may be traced back to pancreatic cancer. Due to medical image scans, a significant number of cancer patients are able to identify abnormalities at an earlier stage. The expensive cost of the necessary gear and infrastructure makes it difficult to disseminate the technology, putting it out of the reach of a lot of people. This article presents detection of pancreatic cancer in CT scan images using machine PSO SVM and image processing. The Gaussian elimination filter is utilized during the image preprocessing stage of the removal of noise from images. The K means algorithm uses a partitioning technique to separate the image into its component parts. The process of identifying objects in an image and determining the regions of interest is aided by image segmentation. The PCA method is used to extract important information from digital photographs. PSO SVM, naive Bayes, and AdaBoost are the algorithms that are used to perform the classification. Accuracy, sensitivity, and specificity of the PSO SVM algorithm are better.
Competing Interests: The authors declare that they have no conflict of interest.
(Copyright © 2022 Arshiya S. Ansari et al.)
Retraction in: Biomed Res Int. 2024 Jan 9;2024:9862575. (PMID: 38230068)
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