View in EDS HTML Full Text PDF Full Text

Fast fourier transform based spectral features for machine learning prediction of gamma passing rates in virtual VMAT PSQA: A feasibility study.

Saved in:
Bibliographic Details
Title: Fast fourier transform based spectral features for machine learning prediction of gamma passing rates in virtual VMAT PSQA: A feasibility study.
Authors: Yan B; School of Instrument Science and Optoelectronics Engineering, Hefei University of Technology, Hefei, Anhui, China.; Department of Radiation Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China., Peng H; School of Instrument Science and Optoelectronics Engineering, Hefei University of Technology, Hefei, Anhui, China., Xue X; Department of Radiation Oncology, Hubei Cancer Hospital, TongJi Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China., Zheng C; School of Instrument Science and Optoelectronics Engineering, Hefei University of Technology, Hefei, Anhui, China., Wu A; Department of Radiation Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China.
Source: Journal of applied clinical medical physics [J Appl Clin Med Phys] 2026 Sep; Vol. 27 (9), pp. e70772.
Publication Type: Journal Article
Journal Info: Publisher: Wiley on behalf of American Association of Physicists in Medicine Country of Publication: United States NLM ID: 101089176 Publication Model: Print Cited Medium: Internet ISSN: 1526-9914 (Electronic) Linking ISSN: 15269914 NLM ISO Abbreviation: J Appl Clin Med Phys Subsets: MEDLINE
Database: MEDLINE Ultimate
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 42661308
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Fast fourier transform based spectral features for machine learning prediction of gamma passing rates in virtual VMAT PSQA: A feasibility study.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Yan+B%22">Yan B</searchLink>; School of Instrument Science and Optoelectronics Engineering, Hefei University of Technology, Hefei, Anhui, China.; Department of Radiation Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China.<br /><searchLink fieldCode="AU" term="%22Peng+H%22">Peng H</searchLink>; School of Instrument Science and Optoelectronics Engineering, Hefei University of Technology, Hefei, Anhui, China.<br /><searchLink fieldCode="AU" term="%22Xue+X%22">Xue X</searchLink>; Department of Radiation Oncology, Hubei Cancer Hospital, TongJi Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.<br /><searchLink fieldCode="AU" term="%22Zheng+C%22">Zheng C</searchLink>; School of Instrument Science and Optoelectronics Engineering, Hefei University of Technology, Hefei, Anhui, China.<br /><searchLink fieldCode="AU" term="%22Wu+A%22">Wu A</searchLink>; Department of Radiation Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101089176%22">Journal of applied clinical medical physics</searchLink> [J Appl Clin Med Phys] 2026 Sep; Vol. 27 (9), pp. e70772.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Wiley+on+behalf+of+American+Association+of+Physicists+in+Medicine%22">Wiley on behalf of American Association of Physicists in Medicine </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101089176 <i>Publication Model: </i>Print <i>Cited Medium: </i>Internet <i>ISSN: </i>1526-9914 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2215269914%22">15269914 </searchLink><i>NLM ISO Abbreviation: </i>J Appl Clin Med Phys <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=42661308
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1002/acm2.70772
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: e70772
    Titles:
      – TitleFull: Fast fourier transform based spectral features for machine learning prediction of gamma passing rates in virtual VMAT PSQA: A feasibility study.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Yan B
      – PersonEntity:
          Name:
            NameFull: Peng H
      – PersonEntity:
          Name:
            NameFull: Xue X
      – PersonEntity:
          Name:
            NameFull: Zheng C
      – PersonEntity:
          Name:
            NameFull: Wu A
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 09
              Text: 2026 Sep
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-electronic
              Value: 1526-9914
          Numbering:
            – Type: volume
              Value: 27
            – Type: issue
              Value: 9
          Titles:
            – TitleFull: Journal of applied clinical medical physics
              Type: main
ResultId 1