Fovea-UNet: detection and segmentation of lymph node metastases in colorectal cancer with deep learning.

Journal: Biomedical engineering online
Published Date:

Abstract

BACKGROUND: Colorectal cancer is one of the most serious malignant tumors, and lymph node metastasis (LNM) from colorectal cancer is a major factor for patient management and prognosis. Accurate image detection of LNM is an important task to help clinicians diagnose cancer. Recently, the U-Net architecture based on convolutional neural networks (CNNs) has been widely used to segment image to accomplish more precise cancer diagnosis. However, the accurate segmentation of important regions with high diagnostic value is still a great challenge due to the insufficient capability of CNN and codec structure in aggregating the detailed and non-local contextual information. In this work, we propose a high performance and low computation solution.

Authors

  • Yajiao Liu
    School of Electrical and Information Engineering, Tianjin University, Tianjin, China.
  • Jiang Wang
    School of Electrical Engineering and Automation, Tianjin University, Tianjin, 300072, People's Republic of China.
  • Chenpeng Wu
    Department of Pathology, Tangshan Gongren Hospital, Tangshan, China.
  • Liyun Liu
    Department of Pathology, Tangshan Gongren Hospital, Tangshan, China.
  • Zhiyong Zhang
  • Haitao Yu
    Department of Fundamental Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi 214122, Jiangsu, China.