Convolutional Neural Network for Automated FLAIR Lesion Segmentation on Clinical Brain MR Imaging.

Journal: AJNR. American journal of neuroradiology
Published Date: Jul 25, 2019

Abstract

BACKGROUND AND PURPOSE: Most brain lesions are characterized by hyperintense signal on FLAIR. We sought to develop an automated deep learning-based method for segmentation of abnormalities on FLAIR and volumetric quantification on clinical brain MRIs across many pathologic entities and scanning parameters. We evaluated the performance of the algorithm compared with manual segmentation and existing automated methods.

Authors

  • M T Duong
    From the Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
  • J D Rudie
    From the Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
  • J Wang
    Joint Laboratory of Modern Agricultural Technology International Cooperation; Key Laboratory of Animal Production, Product Quality, and Security; College of Animal Science and Technology, Jilin Agricultural University, Changchun, China. moa4short@outlook.com.
  • L Xie
    From the Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
  • S Mohan
    From the Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
  • J C Gee
    From the Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
  • A M Rauschecker
    From the Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania. andreas.rauschecker@gmail.com.

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