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Automated Endocardial Border Detection and Left Ventricular Functional Assessment in Echocardiography Using Deep Learning.
Ono, Shunzaburo; Komatsu, Masaaki; Sakai, Akira; Arima, Hideki; Ochida, Mie; Aoyama, Rina; Yasutomi, Suguru; Asada, Ken; Kaneko, Syuzo; Sasano, Tetsuo; Hamamoto, Ryuji.
Afiliación
  • Ono S; Department of Cardiovascular Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan.
  • Komatsu M; Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan.
  • Sakai A; Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan.
  • Arima H; Artificial Intelligence Laboratory, Research Unit, Fujitsu Research, Fujitsu Ltd., 4-1-1 Kamikodanaka, Nakahara-ku, Kawasaki 211-8588, Japan.
  • Ochida M; RIKEN AIP-Fujitsu Collaboration Center, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan.
  • Aoyama R; Department of NCC Cancer Science, Biomedical Science and Engineering Track, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan.
  • Yasutomi S; Department of Cardiovascular Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan.
  • Asada K; Department of Cardiovascular Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan.
  • Kaneko S; Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan.
  • Sasano T; Artificial Intelligence Laboratory, Research Unit, Fujitsu Research, Fujitsu Ltd., 4-1-1 Kamikodanaka, Nakahara-ku, Kawasaki 211-8588, Japan.
  • Hamamoto R; RIKEN AIP-Fujitsu Collaboration Center, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan.
Biomedicines ; 10(5)2022 May 06.
Article en En | MEDLINE | ID: mdl-35625819
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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Guideline Idioma: En Revista: Biomedicines Año: 2022 Tipo del documento: Article País de afiliación: Japón
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Guideline Idioma: En Revista: Biomedicines Año: 2022 Tipo del documento: Article País de afiliación: Japón