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Hardware Implementation of Bone Fracture Detector Using Fuzzy Method Along with Local Normalization Technique

Author

Listed:
  • Abdullah-Al Nahid

    (Macquarie University)

  • Tariq M. Khan

    (Macquarie University)

  • Yinan Kong

    (Macquarie University)

Abstract

Bone fracture detection from the digital image segmentation is a well-known image processing application which is frequently used to process biomedical images. Hardware realization of different image processing algorithm specially utilizing Field Programmable Gate Array (FPGA) has been gained a great interest among the researchers. FPGA has many significant features like spatial and temporal parallelism that best suits for real-time implementation of image processing. To gain the benefit from these characteristics of a FPGA, a new method for bone fracture detection is proposed and its performance is validated through real-time implementation. Simulation results show that the proposed method give superior performance than the existing method.

Suggested Citation

  • Abdullah-Al Nahid & Tariq M. Khan & Yinan Kong, 2017. "Hardware Implementation of Bone Fracture Detector Using Fuzzy Method Along with Local Normalization Technique," Annals of Data Science, Springer, vol. 4(4), pages 533-546, December.
    • Handle: RePEc:spr:aodasc:v:4:y:2017:i:4:d:10.1007_s40745-017-0118-z
    DOI: 10.1007/s40745-017-0118-z
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    References listed on IDEAS

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    1. Izhar Haq & Shahzad Anwar & Kamran Shah & Muhammad Tahir Khan & Shaukat Ali Shah, 2015. "Fuzzy Logic Based Edge Detection in Smooth and Noisy Clinical Images," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-17, September.
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