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CT images processing as one of the stages in knee joint alloarthroplasty

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The main aim of this research is checking the accuracy and ascertaining the quality of a new method of the knee joint alloarthroplasty. The first step of the proposed method is finding the mechanical axis of the lower limb on the basis of fuzzy connectedness concept. In the second step, a radiologist or an orthopedist has to qualify the pathologically modified bone structures within the knee joint. In this way the section planes within femur and tibia are determined. The third step is based on the 3D model of femur and tibia. In order to extract bone structures from the CT slices of the knee joint, the Fuzzy C-Means algorithm with median modification has been implemented. In the next step the impresses of both bones are made and their 3D models are built. On the basis of the CT slices of the knee joint the doctor has to indicate two healthy parts of both bones. Together with the created 3D models they permit building a patient-specific band with two gully holes which are dedicated to serve as location marks for the Kirschner nail.

Original languageEnglish
Title of host publicationProceedings of the 18th International Conference - Mixed Design of Integrated Circuits and Systems, MIXDES 2011
Pages48-51
Number of pages4
Publication statusPublished - 2011
Event18th International Conference - Mixed Design of Integrated Circuits and Systems, MIXDES 2011 - Gliwice, Poland
Duration: 16 Jun 201118 Jun 2011

Publication series

NameProceedings of the 18th International Conference - Mixed Design of Integrated Circuits and Systems, MIXDES 2011

Conference

Conference18th International Conference - Mixed Design of Integrated Circuits and Systems, MIXDES 2011
Country/TerritoryPoland
CityGliwice
Period16/06/1118/06/11

Keywords

  • 3D models of tibia and femur
  • FCM
  • Fuzzy Connectedness
  • mechanical axis of the lower limb

ASJC Scopus subject areas

  • Artificial Intelligence
  • Hardware and Architecture
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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