Localized component analysis for arthritis detection in the trapeziometacarpal joint

  • Authors:

  • Martijn van de Giessen;Sepp de Raedt;Maiken Stilling;Torben B. Hansen;Mario Maas;Geert J. Streekstra;Lucas J. van Vliet;Frans M. Vos

  • Affiliations:

  • Delft University of Technology, The Netherlands and Leiden University Medical Center, The Netherlands and Dept. of Biomed. Engineering and Physics, AMC Amsterdam, The Netherlands;Delft University of Technology, The Netherlands;Dept. of Orthopaedics, Holstebro Regional Hospital, Denmark;Dept. of Orthopaedics, Holstebro Regional Hospital, Denmark;Dept. of Radiology, AMC Amsterdam, The Netherlands;Dept. of Biomed. Engineering and Physics, AMC Amsterdam, The Netherlands;Delft University of Technology, The Netherlands;Delft University of Technology, The Netherlands and Dept. of Radiology, AMC Amsterdam, The Netherlands

  • Venue:
  • MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part II
  • Year:
  • 2011

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Abstract

The trapeziometacarpal joint enables the prehensile function of the thumb. Unfortunately, this joint is vulnerable to osteoarthritis (OA) that typically affects the local shape of the trapezium. A novel, local statistical shape model is defined that employs a differentiable locality measure based on the weighted variance of point coordinates per mode. The simplicity of the function and the smooth derivative enable to quickly determine localized components for densely sampled surfaces. The method is employed to assess a set of 60 trapezia (38 healthy, 22 with OA). The localized components predominantly model regions affected by OA, contrary to shape variations found with PCA. Furthermore, identification of pathological trapezia based on the localized modes of variation is improved compared to PCA.