Diagnosis of Sacroiliitis Through Semi-Supervised Segmentation and Radiomics Feature Analysis of MRI Images.

Journal: Journal of magnetic resonance imaging : JMRI
Published Date: Feb 6, 2025

Abstract

BACKGROUND: Sacroiliitis is a hallmark of ankylosing spondylitis (AS), and early detection plays an important role in managing the condition effectively. MRI is commonly used for diagnosing sacroiliitis, traditional methods often depend on subjective interpretation or limited automation which can introduce variability in diagnoses. The integration of semi-supervised segmentation and radiomics features may reduce reliance on expert interpretation and the need for large annotated datasets, potentially enhancing diagnostic workflows.

Authors

  • Lei Liu
    Department of Science and Technology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
  • Ruotao Zhong
    College of Engineering, Shantou University, Shantou, China.
  • Yuzhen Zhang
  • Haoyang Wan
    Medical College, Shantou University, Shantou, China.
  • Shuju Chen
    Medical College, Shantou University, Shantou, China.
  • Nanfeng Zhang
    Guangdong Hangyu Satellite Technology Co, Shantou, China.
  • Jingjing Liu
    School of Electro-Mechanical Engineering, Xidian University, Xi'an 710071, China.
  • Wei Mei
    Department of Radiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
  • Ruibin Huang
    Department of Radiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.

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