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  • Forsberg, Daniel, et al. (author)
  • Fully automatic measurements of axial vertebral rotation for assessment of spinal deformity in idiopathic scoliosis
  • 2013
  • In: Physics in Medicine and Biology. - : Institute of Physics (IOP). - 0031-9155 .- 1361-6560. ; 58:6, s. 1775-1787
  • Journal article (peer-reviewed)abstract
    • Reliable measurements of spinal deformities in idiopathic scoliosis are vital, since they are used for assessing the degree of scoliosis, deciding upon treatment and monitoring the progression of the disease. However, commonly used two dimensional methods (e.g. the Cobb angle) do not fully capture the three dimensional deformity at hand in scoliosis, of which axial vertebral rotation (AVR) is considered to be of great importance. There are manual methods for measuring the AVR, but they are often time-consuming and related with a high intra- and inter-observer variability. In this paper, we present a fully automatic method for estimating the AVR in images from computed tomography. The proposed method is evaluated on four scoliotic patients with 17 vertebrae each and compared with manual measurements performed by three observers using the standard method by Aaro-Dahlborn. The comparison shows that the difference in measured AVR between automatic and manual measurements are on the same level as the inter-observer difference. This is further supported by a high intraclass correlation coefficient (0.971-0.979), obtained when comparing the automatic measurements with the manual measurements of each observer. Hence, the provided results and the computational performance, only requiring approximately 10 to 15 s for processing an entire volume, demonstrate the potential clinical value of the proposed method.
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Type of publication
journal article (1)
Type of content
peer-reviewed (1)
Author/Editor
Andersson, Mats (1)
Knutsson, Hans (1)
Tropp, Hans (1)
Forsberg, Daniel (1)
Lundström, Claes (1)
Vavruch, Ludvig (1)
University
Linköping University (1)
Language
English (1)
Research subject (UKÄ/SCB)
Engineering and Technology (1)
Medical and Health Sciences (1)
Year

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