Carpal Bone Segmentation Using Fully Convolutional Neural Network.

Journal: Current medical imaging reviews
PMID: 32008525

Abstract

BACKGROUND: Bone Age Assessment (BAA) refers to a clinical procedure that aims to identify a discrepancy between biological and chronological age of an individual by assessing the bone age growth. Currently, there are two main methods of executing BAA which are known as Greulich-Pyle and Tanner-Whitehouse techniques. Both techniques involve a manual and qualitative assessment of hand and wrist radiographs, resulting in intra and inter-operator variability accuracy and time-consuming. An automatic segmentation can be applied to the radiographs, providing the physician with more accurate delineation of the carpal bone and accurate quantitative analysis.

Authors

  • Liang Kim Meng
    Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia.
  • Azira Khalil
    Faculty of Science and Technology, Islamic Science University of Malaysia, 71800, Nilai, Negeri Sembilan, Malaysia.
  • Muhamad Hanif Ahmad Nizar
    Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia.
  • Maryam Kamarun Nisham
    Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia.
  • Belinda Pingguan-Murphy
    Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia.
  • Yan Chai Hum
    Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Bandar Sungai Long, Cheras, 43000 Kajang, Selangor Darul Ehsan, Malaysia.
  • Maheza Irna Mohamad Salim
    Faculty of Biosciences and Medical Engineering, Universiti Teknologi Malaysia, Johor, 81310, Malaysia.
  • Khin Wee Lai
    Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia.

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