Automatic Breast and Fibroglandular Tissue Segmentation in Breast MRI Using Deep Learning by a Fully-Convolutional Residual Neural Network U-Net.

Journal: Academic radiology
Published Date:

Abstract

RATIONALE AND OBJECTIVES: Breast segmentation using the U-net architecture was implemented and tested in independent validation datasets to quantify fibroglandular tissue volume in breast MRI.

Authors

  • Yang Zhang
    Innovative Institute of Chinese Medicine and Pharmacy, Academy for Interdiscipline, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
  • Jeon-Hor Chen
    Department of Radiology, E-Da Hospital and I-Shou University, Kaohsiung 82445, Taiwan and Tu and Yuen Center for Functional Onco-Imaging and Department of Radiological Science, University of California, Irvine, California 92697.
  • Kai-Ting Chang
    Department of Radiological Sciences, John Tu and Thomas Yuen Center for Functional Onco-Imaging, University of California, 164 Irvine Hall, Irvine, CA, 92697-5020.
  • Vivian Youngjean Park
    Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Min Jung Kim
    Department of Pediatrics, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, 16995, South Korea.
  • Siwa Chan
    Department of Medical Imaging, Taichung Tzu-Chi Hospital, Taichung, Taiwan.
  • Peter Chang
    Department of Urology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
  • Daniel Chow
    Department of Radiological Sciences, John Tu and Thomas Yuen Center for Functional Onco-Imaging, University of California, 164 Irvine Hall, Irvine, CA, 92697-5020.
  • Alex Luk
    Department of Radiological Sciences, John Tu and Thomas Yuen Center for Functional Onco-Imaging, University of California, 164 Irvine Hall, Irvine, CA, 92697-5020.
  • Tiffany Kwong
    Department of Radiological Sciences, John Tu and Thomas Yuen Center for Functional Onco-Imaging, University of California, 164 Irvine Hall, Irvine, CA, 92697-5020.
  • Min-Ying Su
    Department of Radiological Sciences, University of California, Irvine, CA 92697, USA.