Detection of aspiration from images of a videofluoroscopic swallowing study adopting deep learning.

Journal: Oral radiology
PMID:

Abstract

OBJECTIVES: A videofluoroscopic swallowing study (VFSS) is conducted to detect aspiration. However, aspiration occurs within a short time and is difficult to detect. If deep learning can detect aspirations with high accuracy, clinicians can focus on the diagnosis of the detected aspirations. Whether VFSS aspirations can be classified using rapid-prototyping deep-learning tools was studied.

Authors

  • Yukihiro Iida
    Department of Oral Radiology, Asahi University School of Dentistry, 1851 Hozumi, Mizuho-city, Gifu, 501-0296, Japan.
  • Janne Näppi
    Massachusetts General Hospital, Harvard Medical School, 25 New Chardon St, Boston, MA, 02114, USA.
  • Tomoya Kitano
    Department of Oral Radiology, Asahi University School of Dentistry, 1851 Hozumi, Mizuho-city, Gifu, 501-0296, Japan.
  • Toru Hironaka
    From the 3D Imaging Research Lab, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon St, Suite 400C, Boston, MA 02114 (R.T., J.J.N., N.K., T.H., H.Y.); Department of Information Science and Technology, National Institute of Technology, Oshima College, Yamaguchi, Japan (R.T.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan (J.O.); Department of Medical Physics, University of Applied Sciences Giessen, Giessen, Germany (N.K.); Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.K.); Department of Surgical Sciences, University of Torino, Turin, Italy (D.R.); and Candiolo Cancer Institute, Fondazione del Piemonte per l'Oncologia-Istituto di Ricovero e Cura a Carattere Scientifico (FPO-IRCCS), Candiolo, Turin, Italy (D.R.).
  • Akitoshi Katsumata
  • Hiroyuki Yoshida
    From the 3D Imaging Research Lab, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon St, Suite 400C, Boston, MA 02114 (R.T., J.J.N., N.K., T.H., H.Y.); Department of Information Science and Technology, National Institute of Technology, Oshima College, Yamaguchi, Japan (R.T.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan (J.O.); Department of Medical Physics, University of Applied Sciences Giessen, Giessen, Germany (N.K.); Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.K.); Department of Surgical Sciences, University of Torino, Turin, Italy (D.R.); and Candiolo Cancer Institute, Fondazione del Piemonte per l'Oncologia-Istituto di Ricovero e Cura a Carattere Scientifico (FPO-IRCCS), Candiolo, Turin, Italy (D.R.).