Deep learning method with a convolutional neural network for image classification of normal and metastatic axillary lymph nodes on breast ultrasonography.

Detalles Bibliográficos
Publicado en:Japanese Journal of Radiology Vol. 40; no. 8; pp. 814 - 823
Autores principales: Ozaki, Jo, Fujioka, Tomoyuki, Yamaga, Emi, Hayashi, Atsushi, Kujiraoka, Yu, Imokawa, Tomoki, Takahashi, Kanae, Okawa, Sayuri, Yashima, Yuka, Mori, Mio, Kubota, Kazunori, Oda, Goshi, Nakagawa, Tsuyoshi, Tateishi, Ukihide
Formato: Journal Article
Publicado: Springer Nature Aug2022
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=158312317&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 158312317
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        18671071
        AUCM
      jtl: Japanese Journal of Radiology
      issn: 18671071
      maglogo: N
    pubinfo:
      dt: Aug2022
      vid: 40
      iid: 8
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        158312317
        155727281
        10.1007/s11604-022-01261-6
        158312317
      ppf: 814
      ppct: 9
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
      tig:
        atl: Deep learning method with a convolutional neural network for image classification of normal and metastatic axillary lymph nodes on breast ultrasonography.
      aug:
        au:
          Ozaki, Jo
          Fujioka, Tomoyuki
          Yamaga, Emi
          Hayashi, Atsushi
          Kujiraoka, Yu
          Imokawa, Tomoki
          Takahashi, Kanae
          Okawa, Sayuri
          Yashima, Yuka
          Mori, Mio
          Kubota, Kazunori
          Oda, Goshi
          Nakagawa, Tsuyoshi
          Tateishi, Ukihide
        affil: Department of Diagnostic Radiology, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, 113-8510, Tokyo, Japan
      sug:
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
      ab:
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N