SAFARI: shape analysis for AI-segmented images.

Journal: BMC medical imaging
Published Date: Jul 22, 2022

Abstract

BACKGROUND: Recent developments to segment and characterize the regions of interest (ROI) within medical images have led to promising shape analysis studies. However, the procedures to analyze the ROI are arbitrary and vary by study. A tool to translate the ROI to analyzable shape representations and features is greatly needed.

Authors

  • Esteban Fernández
    Department of Mathematical Sciences, The University of Texas at Dallas, Richardson, TX, USA.
  • Shengjie Yang
    Quantitative Biomedical Research Center, Department of Population and Data Sciences, The University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Sy Han Chiou
    Department of Mathematical Sciences, The University of Texas at Dallas, Richardson, TX, USA.
  • Chul Moon
    Department of Statistical Science, Southern Methodist University, Dallas, TX, USA.
  • Cong Zhang
    School of Civil Engineering, Southeast University, Nanjing 210096, China.
  • Bo Yao
    Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China.
  • Guanghua Xiao
  • Qiwei Li
    Department of General Surgery, South Campus, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.

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