PSO-Based Evolutionary Approach to Optimize Head and Neck Biomedical Image to Detect Mesothelioma Cancer.
Mesothelioma is a form of cancer that is aggressive and fatal. It is a thin layer of tissue that covers the majority of the patient's internal organs. The treatments are available; however, a cure is not attainable for the majority of patients. So, a lot of research is being done on detection of mes...
| Publicado en: | BioMed Research International pp. 1 - 13 |
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| Autores principales: | , , , , , , |
| Formato: | algorithm diagnostic images research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
8/5/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=158380398&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 158380398 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 8/5/2022 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 158380398 158380398 158380398 10.1155/2022/3618197 158380398 ppf: 1 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: PSO-Based Evolutionary Approach to Optimize Head and Neck Biomedical Image to Detect Mesothelioma Cancer. aug: au: Praveen, Sheeba Tyagi, Neha Singh, Bhagwant Karetla, Girija Rani Thalor, Meenakshi Anurag Joshi, Kapil Tsegaye, Melkamu affil: Integral University Lucknow, India sug: subj: Algorithms Utilization Mesothelioma Diagnosis Head and Neck Neoplasms Diagnosis Diagnostic Imaging Methods Image Processing, Computer Assisted India ab: Mesothelioma is a form of cancer that is aggressive and fatal. It is a thin layer of tissue that covers the majority of the patient's internal organs. The treatments are available; however, a cure is not attainable for the majority of patients. So, a lot of research is being done on detection of mesothelioma cancer using various different approaches; but this paper focuses on optimization techniques for optimizing the biomedical images to detect the cancer. With the restricted number of samples in the medical field, a Relief-PSO head and mesothelioma neck cancer pathological image feature selection approach is proposed. The approach reduces multilevel dimensionality. To begin, the relief technique picks different feature weights depending on the relationship between features and categories. Second, the hybrid binary particle swarm optimization (HBPSO) is suggested to automatically determine the optimum feature subset for candidate feature subsets. The technique outperforms seven other feature selection algorithms in terms of morphological feature screening, dimensionality reduction, and classification performance. pubtype: Academic Journal doctype: algorithm diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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