A Novel Deep Learning Approach with a 3D Convolutional Ladder Network for Differential Diagnosis of Idiopathic Normal Pressure Hydrocephalus and Alzheimer's Disease.

Journal: Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Published Date: Dec 1, 2020

Abstract

PURPOSE: Idiopathic normal pressure hydrocephalus (iNPH) and Alzheimer's disease (AD) are geriatric diseases and common causes of dementia. Recently, many studies on the segmentation, disease detection, or classification of MRI using deep learning have been conducted. The aim of this study was to differentiate iNPH and AD using a residual extraction approach in the deep learning method.

Authors

  • Ryusuke Irie
    Department of Radiology, Juntendo University School of Medicine.
  • Yujiro Otsuka
    Department of Radiology, Juntendo University School of Medicine.
  • Akifumi Hagiwara
    Department of Radiology, Juntendo University School of Medicine.
  • Koji Kamagata
  • Kouhei Kamiya
    Department of Radiology, The University of Tokyo.
  • Michimasa Suzuki
    Department of Radiology, Juntendo University School of Medicine.
  • Akihiko Wada
  • Tomoko Maekawa
    Department of Radiology, Juntendo University School of Medicine.
  • Shohei Fujita
    Department of Radiology, Juntendo University School of Medicine.
  • Shimpei Kato
    Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Madoka Nakajima
    Department of Neurosurgery, Juntendo University School of Medicine.
  • Masakazu Miyajima
    Department of Neurosurgery, Juntendo Tokyo Koto Geriatric Medical Center.
  • Yumiko Motoi
    Department of Neurology, Juntendo University School of Medicine.
  • Osamu Abe
    From the Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan 113-8655.
  • Shigeki Aoki

Keywords

External Resources

Popular Topics
Recent Journals