Improving Sensitivity of Arterial Spin Labeling Perfusion MRI in Alzheimer's Disease Using Transfer Learning of Deep Learning‐Based ASL Denoising

Abstract

Arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) denoising through deep learning (DL) often faces insufficient training data from patients. One solution is to train DL models using healthy subjects' data which are more widely available and transfer them to patients' data.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 06, 2021
Source ID
10.1002/jmri.27984

Entities

People

  • Aldo Camargo
  • Danfeng Xie
  • David Dreizin
  • Donghui Song
  • Elias R. Melhem
  • Jean Jeudy
  • Lei Zhang
  • The Alzheimer’s Disease Neuroimaging Initiative*
  • Tong Lu
  • Yiran Li
  • Ze Wang

Organizations

  • AbbVie
  • Alzheimer's Association
  • Alzheimer's Drug Discovery Foundation
  • BioClinica
  • Biogen
  • Canadian Institutes of Health Research
  • Chiron Corporation
  • Eli Lilly and Company
  • Foundation for the National Institutes of Health
  • GE HealthCare
  • Hoffmann-La Roche
  • Laboratoires Servier
  • Lundbeck
  • Merck & Co.
  • National Institute of Biomedical Imaging and Bioengineering
  • National Institute on Aging
  • National Institutes of Health
  • Norman Cousins Center for Psychoneuroimmunology
  • Northern California Institute for Research and Education
  • Pfizer
  • Roche (United States)
  • Takeda Pharmaceutical Company
  • United States Department of Defense
  • University of Maryland
  • University of Maryland School of Medicine

Tags

Fields of Study

  • Medicine

Readers

  • Computer Vision.
  • Medical Imaging.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks