RRM-TransUNet: Deep-Learning Driven Interactive Model for Precise Pancreas Segmentation in CT Images.

Journal: The international journal of medical robotics + computer assisted surgery : MRCAS
PMID: 40209153

Abstract

BACKGROUND: Pancreatic diseases such as cancer and pancreatitis pose significant health risks. Early detection requires precise segmentation results. Fully automatic segmentation algorithms cannot integrate clinical expertise and correct output errors, while interactive methods can offer a better chance for higher accuracy and reliability.

Authors

  • Yulan Wang
    Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences , 555 Zuchongzhi Road, Shanghai 201203, China.
  • Weimin Liu
    State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China.
  • Peng Yu
    College of Life Science, Northwest Normal University, Lanzhou, 730070, Gansu, People's Republic of China.
  • Xin Huang
    Department of ophthalmology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China.
  • Junjun Pan
    Department of Mathematics, The University of Hong Kong, Pokfulam, Hong Kong. Electronic address: junjpan@hku.hk.

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