Intelligent noninvasive meningioma grading with a fully automatic segmentation using interpretable multiparametric deep learning.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: To establish a robust interpretable multiparametric deep learning (DL) model for automatic noninvasive grading of meningiomas along with segmentation.

Authors

  • Yohan Jun
    School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea.
  • Yae Won Park
    Department of Radiology, Ewha Womans University College of Medicine, Seoul, Korea.
  • Hyungseob Shin
    School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea.
  • Yejee Shin
    Medical Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei University, 50, Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
  • Jeong Ryong Lee
    Medical Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei University, 50, Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
  • Kyunghwa Han
    From the Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea (S.H.P.); and Department of Radiology, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea (K.H.).
  • Sung Soo Ahn
    Department of Radiology, Severance Hospital, Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, Seoul, Korea. sungsoo@yuhs.ac.
  • Soo Mee Lim
    Department of Radiology, Ewha Womans University Seoul Hospital, Seoul, Korea.
  • Dosik Hwang
    School of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea. dosik.hwang@yonsei.ac.kr.
  • Seung-Koo Lee
    Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea.