Deeply self-supervised contour embedded neural network applied to liver segmentation.

Journal: Computer methods and programs in biomedicine
Published Date: Mar 15, 2020

Abstract

OBJECTIVE: Herein, a neural network-based liver segmentation algorithm is proposed, and its performance was evaluated using abdominal computed tomography (CT) images.

Authors

  • Minyoung Chung
    School of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Korea. Electronic address: chungmy@cglab.snu.ac.kr.
  • Jingyu Lee
    School of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Korea. Electronic address: leejingyu@cglab.snu.ac.kr.
  • Minkyung Lee
    School of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Korea. Electronic address: mklee317@cglab.snu.ac.kr.
  • Jeongjin Lee
    School of Computer Science and Engineering, Soongsil University, Seoul, Korea.
  • Yeong-Gil Shin
    School of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Korea. Electronic address: yshin@snu.ac.kr.

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