A deep learning algorithm for white matter hyperintensity lesion detection and segmentation.

Journal: Neuroradiology
Published Date: Apr 1, 2022

Abstract

PURPOSE: White matter hyperintensity (WMHI) lesions on MR images are an important indication of various types of brain diseases that involve inflammation and blood vessel abnormalities. Automated quantification of the WMHI can be valuable for the clinical management of patients, but existing automated software is often developed for a single type of disease and may not be applicable for clinical scans with thick slices and different scanning protocols. The purpose of the study is to develop and validate an algorithm for automatic quantification of white matter hyperintensity suitable for heterogeneous MRI data with different disease types.

Authors

  • Yajing Zhang
    MR Clinical Science, Philips Healthcare (Suzhou), Suzhou, China.
  • Yunyun Duan
    Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
  • Xiaoyang Wang
    Department of Radiology, Ruian People's Hospital, Zhejiang, 325200, China.
  • Zhizheng Zhuo
    Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
  • Sven Haller
    Department of Surgical Sciences, Radiology, Uppsala University, Sweden.
  • Frederik Barkhof
    MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, the Netherlands.
  • Yaou Liu
    Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, PR China; Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100050, PR China.

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