Literature DB >> 34993056

Validation of watershed-based segmentation of the cartilage surface from sequential CT arthrography scans.

Mary E Hall1, Marianne S Black1,2, Garry E Gold2,3, Marc E Levenston1,2,3.   

Abstract

BACKGROUND: This study investigated the utility of a 2-dimensional watershed algorithm for identifying the cartilage surface in computed tomography (CT) arthrograms of the knee up to 33 minutes after an intra-articular iohexol injection as boundary blurring increased.
METHODS: A 2D watershed algorithm was applied to CT arthrograms of 3 bovine stifle joints taken 3, 8, 18, and 33 minutes after iohexol injection and used to segment tibial cartilage. Thickness measurements were compared to a reference standard thickness measurement and the 3-minute time point scan.
RESULTS: 77.2% of cartilage thickness measurements were within 0.2 mm (1 voxel) of the thickness calculated in the reference scan at the 3-minute time point. 42% fewer voxels could be segmented from the 33-minute scan than the 3-minute scan due to diffusion of the contrast agent out of the joint space and into the cartilage, leading to blurring of the cartilage boundary. The traced watershed lines were closer to the location of the cartilage surface in areas where tissues were in direct contact with each other (cartilage-cartilage or cartilage-meniscus contact).
CONCLUSIONS: The use of watershed dam lines to guide cartilage segmentation shows promise for identifying cartilage boundaries from CT arthrograms in areas where soft tissues are in direct contact with each other. 2022 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Entities:  

Keywords:  Computed tomography (CT); arthrography; image processing; knee; segmentation

Year:  2022        PMID: 34993056      PMCID: PMC8666781          DOI: 10.21037/qims-20-1062

Source DB:  PubMed          Journal:  Quant Imaging Med Surg        ISSN: 2223-4306


  38 in total

1.  Upright weight-bearing CT of the knee during flexion: changes of the patellofemoral and tibiofemoral articulations between 0° and 120°.

Authors:  Anna Hirschmann; Florian M Buck; Ramin Herschel; Christian W A Pfirrmann; Sandro F Fucentese
Journal:  Knee Surg Sports Traumatol Arthrosc       Date:  2015-11-04       Impact factor: 4.342

2.  Coupled tomography and distinct-element-method approach to exploring the granular media microstructure in a jamming hourglass.

Authors:  M Tsukahara; S Mitrovic; V Gajdosik; G Margaritondo; L Pournin; M Ramaioli; D Sage; Y Hwu; M Unser; Th M Liebling
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2008-06-25

3.  Fiducial marker-based correction for involuntary motion in weight-bearing C-arm CT scanning of knees. Part I. Numerical model-based optimization.

Authors:  Jang-Hwan Choi; Rebecca Fahrig; Andreas Keil; Thor F Besier; Saikat Pal; Emily J McWalter; Gary S Beaupré; Andreas Maier
Journal:  Med Phys       Date:  2013-09       Impact factor: 4.071

4.  Clinically applied CT arthrography to measure the sulphated glycosaminoglycan content of cartilage.

Authors:  M Siebelt; J van Tiel; J H Waarsing; T M Piscaer; M van Straten; R Booij; M L Dijkshoorn; G J Kleinrensink; J A N Verhaar; G P Krestin; H Weinans; E H G Oei
Journal:  Osteoarthritis Cartilage       Date:  2011-07-23       Impact factor: 6.576

5.  Contrast agent electrostatic attraction rather than repulsion to glycosaminoglycans affords a greater contrast uptake ratio and improved quantitative CT imaging in cartilage.

Authors:  P N Bansal; R C Stewart; V Entezari; B D Snyder; M W Grinstaff
Journal:  Osteoarthritis Cartilage       Date:  2011-04-21       Impact factor: 6.576

6.  Cationic contrast agents improve quantification of glycosaminoglycan (GAG) content by contrast enhanced CT imaging of cartilage.

Authors:  Prashant N Bansal; Neel S Joshi; Vahid Entezari; Bethany C Malone; Rachel C Stewart; Brian D Snyder; Mark W Grinstaff
Journal:  J Orthop Res       Date:  2010-12-23       Impact factor: 3.494

7.  Extremity cone-beam CT for evaluation of medial tibiofemoral osteoarthritis: Initial experience in imaging of the weight-bearing and non-weight-bearing knee.

Authors:  Gaurav K Thawait; Shadpour Demehri; Abdullah AlMuhit; Wojciech Zbijweski; John Yorkston; Filippo Del Grande; Bashir Zikria; John A Carrino; Jeffrey H Siewerdsen
Journal:  Eur J Radiol       Date:  2015-09-12       Impact factor: 3.528

8.  Quantitative assessment of articular cartilage morphology via EPIC-microCT.

Authors:  L Xie; A S P Lin; M E Levenston; R E Guldberg
Journal:  Osteoarthritis Cartilage       Date:  2008-09-11       Impact factor: 6.576

9.  Diffusion and near-equilibrium distribution of MRI and CT contrast agents in articular cartilage.

Authors:  Tuomo S Silvast; Harri T Kokkonen; Jukka S Jurvelin; Thomas M Quinn; Miika T Nieminen; Juha Töyräs
Journal:  Phys Med Biol       Date:  2009-10-28       Impact factor: 3.609

10.  In vivo diagnostics of human knee cartilage lesions using delayed CBCT arthrography.

Authors:  Harri T Kokkonen; Juha-Sampo Suomalainen; Antti Joukainen; Heikki Kröger; Joonas Sirola; Jukka S Jurvelin; Jari Salo; Juha Töyräs
Journal:  J Orthop Res       Date:  2013-11-19       Impact factor: 3.494

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  2 in total

1.  Improved Watershed Algorithm-Based Microscopic Images Combined with Meibomian Gland Microprobe in the Treatment of Demodectic Blepharitis.

Authors:  Lanying Liu; Shengfu Yang; Min Zhu; Min Wang; Xin Wei
Journal:  Comput Math Methods Med       Date:  2022-06-08       Impact factor: 2.809

2.  Graphical Image Region Extraction with K-Means Clustering and Watershed.

Authors:  Sandra Jardim; João António; Carlos Mora
Journal:  J Imaging       Date:  2022-06-08
  2 in total

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