Automatic Liver Tumor Segmentation on Dynamic Contrast Enhanced MRI Using 4D Information: Deep Learning Model Based on 3D Convolution and Convolutional LSTM.

Journal: IEEE transactions on medical imaging
Published Date: Sep 30, 2022

Abstract

OBJECTIVE: Accurate segmentation of liver tumors, which could help physicians make appropriate treatment decisions and assess the effectiveness of surgical treatment, is crucial for the clinical diagnosis of liver cancer. In this study, we propose a 4-dimensional (4D) deep learning model based on 3D convolution and convolutional long short-term memory (C-LSTM) for hepatocellular carcinoma (HCC) lesion segmentation.

Authors

  • Rencheng Zheng
    Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
  • Qidong Wang
  • Shuangzhi Lv
    Radiology Department, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
  • Cuiping Li
  • ChengYan Wang
  • Weibo Chen
    Philips Healthcare, Shanghai, People's Republic of China.
  • He Wang
    Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, China International Neuroscience Institute, Beijing, China.

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