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Joint Image Extraction Algorithm and Super-Resolution Algorithm for Rheumatoid Arthritis Medical Examinations

  • Tomio Goto
  • Yoshiki Sano
  • Takuma Mori
  • Masato Shimizu
  • Koji Funahashi
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 98)

Abstract

Super-resolution techniques have been widely used in fields such as television, aerospace imaging, and medical imaging. In medical imaging, X-rays commonly have low resolution and a significant amount of noise, because radiation levels are minimized to maintain patient safety. So, we proposed a novel super-resolution method for X-ray images, and a novel measurement algorithm for treatment of rheumatoid arthritis (RA) using X-ray images generated by our proposed super-resolution method. However, in our proposed system, there are several operations to do by doctors manually, and it is hard for them. By utilizing image recognition technology, it is possible to extract joint images from X-ray images automatically. In this paper, we will discuss an algorithm to extract joint images from X-ray images automatically. Experimental results show that correct joint images will be obtained for our proposed method. Therefore, our proposed measurement algorithm is effective for RA medical examinations.

Keywords

Image extraction Joint space distance Rheumatoid arthritis Medical examinations 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Tomio Goto
    • 1
  • Yoshiki Sano
    • 1
  • Takuma Mori
    • 1
  • Masato Shimizu
    • 1
  • Koji Funahashi
    • 2
  1. 1.Department of Computer Science and EngineeringNagoya Institute of TechnologyNagoyaJapan
  2. 2.Orthopaedic SurgeryKariya Toyota General HospitalKariyaJapan

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