Enhancing Brain Metastases Detection and Segmentation in Black-Blood MRI Using Deep Learning and Segment Anything Model (SAM).

Journal: Yonsei medical journal
Published Date: Aug 1, 2025

Abstract

PURPOSE: Black-blood (BB) magnetic resonance images (MRI) offer superior image contrast for the detection and segmentation of brain metastases (BMs). This study investigated the efficacy and accuracy of deep learning (DL) architectures and post-processing for BMs detection and segmentation with BB images.

Authors

  • Sang Kyun Yoo
    Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, 50-1 Yonsei-Ro, Seodaemun-gu, Seoul, 03722, Korea.
  • Tae Hyung Kim
    TheragenBio, Seongnam, Republic of Korea.
  • Jin Sung Kim
    Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South 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.
  • Eui Hyun Kim
    Department of Neurosurgery, Yonsei University College of Medicine, Seoul, South Korea.
  • Wonmo Sung
    Department of Biomedical Engineering and of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
  • Hojin Kim
    Department of Radiation Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 05505, Republic of Korea.
  • Hong In Yoon
    Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, South Korea; Brain Research Institute, Yonsei University College of Medicine, Seoul, Korea. Electronic address: yhi0225@yuhs.ac.

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