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Application of Neural Networks in Assessing Changes around Implant after Total Hip Arthroplasty

  • Arkadiusz Szarek
  • Marcin Korytkowski
  • Leszek Rutkowski
  • Rafał Scherer
  • Janusz Szyprowski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7268)

Abstract

Bone and joint diseases afflict more and more younger people. This is due to the work habits, quality and intensity of life, diet and individual factors. Hip arthroplasty is a surgery to remove the pain and to allow the patient to return to normal functioning in society. Endoprosthesoplasty brings the desired effect, but the life span of contemporary endoprosthesis is still not satisfactory. Clinical studies have shown that the introduction of the implant to the bone causes a number of changes within the bone – implant contact. The correct prediction of changes around the implant allows to plan the surgery and to identify hazardous areas where bone decalcification and loss of primary stability in implant can occur.

Keywords

Neural Network Fuzzy System Soft Computing Hazardous Area Work Habit 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Arkadiusz Szarek
    • 1
  • Marcin Korytkowski
    • 2
    • 3
  • Leszek Rutkowski
    • 2
    • 4
  • Rafał Scherer
    • 2
  • Janusz Szyprowski
    • 5
  1. 1.Institute of Metal Working and Forming, Quality Engineering and BioengineeringCzȩstochowa University of TechnologyPoland
  2. 2.Department of Computer EngineeringCzȩstochowa University of TechnologyCzȩstochowaPoland
  3. 3.Olsztyn Academy of Computer Science and ManagementOlsztynPoland
  4. 4.SWSPiZ Academy of ManagementInstitute of Information TechnologyŁódźPoland
  5. 5.Orthopedics and Traumatic Surgery Department of NMP Voivodship Specialist HospitalCzȩstochowaPoland

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