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A multi-center milestone study of clinical vertebral CT segmentation

Yao, Jianhua (författare)
NIH, MD 20892 USA
Burns, Joseph E. (författare)
University of Calif Irvine, CA 92688 USA
Forsberg, Daniel (författare)
Linköpings universitet,Medie- och Informationsteknik,Tekniska högskolan,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Sectra, Linkoping, Sweden
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Seitel, Alexander (författare)
University of British Columbia, Canada
Rasoulian, Abtin (författare)
University of British Columbia, Canada
Abolmaesumi, Purang (författare)
University of British Columbia, Canada
Hammernik, Kerstin (författare)
Graz University of Technology, Austria
Urschler, Martin (författare)
Ludwig Boltzmann Institute Clin Forens Imaging, Austria
Ibragimov, Bulat (författare)
University of Ljubljana, Slovenia
Korez, Robert (författare)
University of Ljubljana, Slovenia
Vrtovec, Tomaz (författare)
University of Ljubljana, Slovenia
Castro-Mateos, Isaac (författare)
University of Sheffield, England
Pozo, Jose M. (författare)
University of Sheffield, England
Frangi, Alejandro F. (författare)
University of Sheffield, England
Summers, Ronald M. (författare)
NIH, MD 20892 USA
Li, Shuo (författare)
GE Healthcare, Canada; University of Western Ontario, Canada
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 (creator_code:org_t)
PERGAMON-ELSEVIER SCIENCE LTD, 2016
2016
Engelska.
Ingår i: Computerized Medical Imaging and Graphics. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0895-6111 .- 1879-0771. ; 49, s. 16-28
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • A multiple center milestone study of clinical vertebra segmentation is presented in this paper. Vertebra segmentation is a fundamental step for spinal image analysis and intervention. The first half of the study was conducted in the spine segmentation challenge in 2014 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) Workshop on Computational Spine Imaging (CSI 2014). The objective was to evaluate the performance of several state-of-the-art vertebra segmentation algorithms on computed tomography (CT) scans using ten training and five testing dataset, all healthy cases; the second half of the study was conducted after the challenge, where additional 5 abnormal cases are used for testing to evaluate the performance under abnormal cases. Dice coefficients and absolute surface distances were used as evaluation metrics. Segmentation of each vertebra as a single geometric unit, as well as separate segmentation of vertebra substructures, was evaluated. Five teams participated in the comparative study. The top performers in the study achieved Dice coefficient of 0.93 in the upper thoracic, 0.95 in the lower thoracic and 0.96 in the lumbar spine for healthy cases, and 0.88 in the upper thoracic, 0.89 in the lower thoracic and 0.92 in the lumbar spine for osteoporotic and fractured cases. The strengths and weaknesses of each method as well as future suggestion for improvement are discussed. This is the first multi-center comparative study for vertebra segmentation methods, which will provide an up-to-date performance milestone for the fast growing spinal image analysis and intervention. (C) 2016 Elsevier Ltd. All rights reserved.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)

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