Radiomics approach with deep learning for predicting T4 obstructive colorectal cancer using CT image.

Journal: Abdominal radiology (New York)
Published Date: Mar 1, 2023

Abstract

OBJECTIVES: Patients with T4 obstructive colorectal cancer (OCC) have a high mortality rate. Therefore, an accurate distinction between T4 and T1-T3 (NT4) in OCC is an important part of preoperative evaluation, especially in the emergency setting. This paper introduces three models of radiomics, deep learning, and deep learning-based radiomics to identify T4 OCC.

Authors

  • Lin Pan
    School of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China.
  • Tian He
    Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Zihan Huang
    Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Shuai Chen
    State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
  • Junrong Zhang
    Department of Emergency Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China.
  • Shaohua Zheng
    School of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China.
  • Xianqiang Chen
    Department of Emergency Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China. cxq760818@163.com.

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