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Novel fast semi-automated software to segment cartilage for knee MR acquisitions.

Novel fast semi-automated software to segment cartilage for knee MR acquisitions. Research Abstract Details 

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  • Novel fast semi-automated software to segment cartilage for knee MR acquisitions. Abstract Text:

    j duryeaJ Duryea,g neumannG Neumann,m h bremM H Brem,w kohW Koh,f noorbakhshF Noorbakhsh,r d jacksonR D Jackson,j yuJ Yu,c b eatonC B Eaton,p langP Lang,

    OBJECTIVE: Validation of a new fast software technique to segment the cartilage on knee magnetic resonance (MR) acquisitions. Large studies of knee osteoarthritis (OA) will require fast and reproducible methods to quantify cartilage changes for knee MR data. In this report we document and measure the reproducibility and reader time of a software-based technique to quantify the volume and thickness of articular cartilage on knee MR images. METHODS: The software was tested on a set of duplicate sagittal three-dimensional (3D) dual echo steady state (DESS) acquisitions from 15 (8 OA, 7 normal) subjects. The repositioning, inter-reader, and intra-reader reproducibility of the cartilage volume (VC) and thickness (ThC) were measured independently as well as the reader time for each cartilage plate. The root-mean square coefficient of variation (RMSCoV) was used as metric to quantify the reproducibility of VC and mean ThC. RESULTS: The repositioning RMSCoV was as follows: VC=2.0% and ThC=1.2% (femur), VC=2.9% and ThC=1.6% (medial tibial plateau), VC=5.5% and ThC=2.4% (lateral tibial plateau), and VC=4.6% and ThC=2.3% (patella). RMSCoV values were higher for the inter-reader reproducibility (VC: 2.5-8.6%) (ThC: 1.9-5.2%) and lower for the intra-reader reproducibility (VC: 1.6-2.5%) (ThC: 1.2-1.9%). The method required an average of 75.4min per knee. CONCLUSIONS: We have documented a fast reproducible semi-automated software method to segment articular cartilage on knee MR acquisitions.

    Novel fast semi-automated software to segment cartilage for knee MR acquisitions. Publishing Authors By Initials

    j duryeaJ Duryea,g neumannG Neumann,mh bremMH Brem,w kohW Koh,f noorbakhshF Noorbakhsh,rd jacksonRD Jackson,j yuJ Yu,cb eatonCB Eaton,p langP Lang,

    For similar information science: computing methodologies: software research abstracts see: information science: computing methodologies: software research

    PUBMED ID PMID:

    MEDLINE DATE:

    Novel fast semi-automated software to segment cartilage for knee MR acquisitions. Journal Published:

    PUBLICATION TYPE: Research Support, N.I.H., Intr

    Journal: Osteoarthritis and cartilage / OARS, Osteoarthriti

    VOLUME: 15

    Page Numbers: 487-92

    Journal Abbreviation:

    ISSN: 1063-4584

    DAY: 22

    MONTH: 12

    YEAR: 2006

    Novel fast semi-automated software to segment cartilage for knee MR acquisitions. Information

    Number of References:

    LANGUAGE: eng

    NlmUniqueID: 9305697

    Novel fast semi-automated software to segment cartilage for knee MR acquisitions. Keywords Mesh Terms:

    KEYWORDS: Software

    MESH TERMS: pathology

    Chemical & Substance for Abstract: Novel fast semi-automated software to segment cartilage for knee MR acquisitions. Information

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    Grant and Affiliation Information for Novel fast semi-automated software to segment cartilage for knee MR acquisitions.

    AFFILIATION: Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA. jduryea@bwh.harvard.edu

    Country: England

    England Research PublicationEngland Research Publication

    AGENCY: United States NIAMS

    GRANT: N01-AR-2-2262

    ACRONYM: AR

    MEDLINETA: Osteoarthritis Cartilage

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