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Radiostereometry Using NURBS Implant Models
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
2018 (engelsk)Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
Abstract [en]

Radiostereometric analysis (RSA) is a method used for determining migration and wear of orthopaedic implants through measurements performed in radiographs. There are two approaches of RSA: marker-based and model-based (MBRSA). Marker-based RSA is the conventional and most accurate method. However, it requires markers to be inserted or attached to the implants. MBRSA avoids using markers by employing 3D geometric models of the implants. State-of-the-art methods for model-based RSA use either elementary geometric shapes (EGS) or triangulated surface (TS) models. EGS models are smooth but not generic. They can only model implants that have simple canonical shapes. In contrast, TS models are generic but not smooth. They can model both basic and free-form shapes but not as smooth as EGS models. The degree of smoothness depends on the number of triangles used.

In this thesis, we introduce Non-uniform Rational B-Splines (NURBS) models that are both generic and smooth. Two algorithms were developed: 1) A fitting algorithm that fits multi-patch NURBS models to unorganized point clouds representing the surface of the implants. 2) An RSA algorithm that fits the NURBS models to points measured in radiographs. To evaluate the algorithms, NURBS models of a femoral head and an acetabular component were generated by the fitting algorithm. The femoral head penetration into the acetabular component was computed by the NURBS-based RSA algorithm using clinical double examinations for a single hip replacement patient. The precision of the NURBS-based RSA algorithm for computing the femoral head penetrationis comparable to the reported precision of a state-of-the-art EGS based RSA algorithm for solving the same problem. This result suggests that NURBS models can be a good alternative to the current models used in MBRSA.

sted, utgiver, år, opplag, sider
2018. , s. 61
Serie
UMNAD ; 1155
HSV kategori
Identifikatorer
URN: urn:nbn:se:umu:diva-152565OAI: oai:DiVA.org:umu-152565DiVA, id: diva2:1255363
Utdanningsprogram
Master's Programme in Computing Science
Veileder
Examiner
Tilgjengelig fra: 2018-10-12 Laget: 2018-10-12 Sist oppdatert: 2018-10-12bibliografisk kontrollert

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