Application of neural networks in assessing changes around implant after total hip arthroplasty

  • Authors:

  • Arkadiusz Szarek;Marcin Korytkowski;Leszek Rutkowski;Rafał Scherer;Janusz Szyprowski

  • Affiliations:

  • Institute of Metal Working and Forming, Quality Engineering and Bioengineering, Czȩstochowa University of Technology, Poland;Department of Computer Engineering, Czȩstochowa University of Technology, Czȩstochowa, Poland and Olsztyn Academy of Computer Science and Management, Olsztyn, Poland;Department of Computer Engineering, Czȩstochowa University of Technology, Czȩstochowa, Poland and SWSPiZ Academy of Management, Institute of Information Technology, Łódź, ...;Department of Computer Engineering, Czȩstochowa University of Technology, Czȩstochowa, Poland;Orthopedics and Traumatic Surgery Department of NMP Voivodship Specialist Hospital, Czȩstochowa, Poland

  • Venue:
  • ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
  • Year:
  • 2012

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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.