Robust performance of deep learning for automatic detection and segmentation of brain metastases using three-dimensional black-blood and three-dimensional gradient echo imaging.

Journal: European radiology
PMID:

Abstract

OBJECTIVES: To evaluate whether a deep learning (DL) model using both three-dimensional (3D) black-blood (BB) imaging and 3D gradient echo (GRE) imaging may improve the detection and segmentation performance of brain metastases compared to that using only 3D GRE imaging.

Authors

  • Yae Won Park
    Department of Radiology, Ewha Womans University College of Medicine, Seoul, Korea.
  • Yohan Jun
    School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea.
  • Yangho Lee
    Department of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South 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.).
  • Chansik An
    Research Institute, National Health Insurance Service Ilsan Hospital, Goyang, Korea.
  • 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.
  • 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.