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    Diagnostic of Injury Risk in the Anterior Cruciate Ligament Based on Shape Context Description of the Intercondylar Notch Curvature

    Source: Journal of Engineering and Science in Medical Diagnostics and Therapy:;2022:;volume( 005 ):;issue: 002::page 21001-1
    Author:
    Dias, João Paulo
    ,
    Bhuiyan, Ariful
    ,
    Shamim, Nabila
    DOI: 10.1115/1.4053063
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: An estimated number of 300,000 new anterior cruciate ligament (ACL) injuries occur each year in the United States. Recent studies have pointed out a correlation between the curvature of the femur intercondylar notch and the risk of noncontact ACL injury. Although several magnetic resonance (MR) imaging-based ACL diagnostics methods have already been proposed in the literature, most of them are based on machine learning or deep learning strategies, which are computationally expensive. In this paper, we propose a diagnostics framework for the risk of injury in the ACL based on the application of the inner-distance shape context (IDSC) to describe the curvature of the intercondylar notch from MR images. First, the contours of the intercondylar notch curvature from 91 MR images of the distal end of the femur (70 healthy and 21 with confirmed ACL injury) were extracted manually using standard image processing tools. Next, the IDSC was applied to calculate the similarity factor between the extracted contours and reference standard curvatures. Finally, probability density functions of the similarity factor data were obtained through parametric statistical inference, and the accuracy of the ACL injury risk diagnostics framework was assessed using receiver operating characteristic analysis (ROC). The overall results for the area under the curve (AUC) showed that the method reached a maximum accuracy of about 66%. Furthermore, the sensitivity and specificity results showed that an optimum discrimination threshold value for the similarity factor can be pursued that minimizes the incidence of false positives and false negatives simultaneously.
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      Diagnostic of Injury Risk in the Anterior Cruciate Ligament Based on Shape Context Description of the Intercondylar Notch Curvature

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4285471
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    contributor authorDias, João Paulo
    contributor authorBhuiyan, Ariful
    contributor authorShamim, Nabila
    date accessioned2022-05-08T09:41:55Z
    date available2022-05-08T09:41:55Z
    date copyright2/17/2022 12:00:00 AM
    date issued2022
    identifier issn2572-7958
    identifier otherjesmdt_005_02_021001.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4285471
    description abstractAn estimated number of 300,000 new anterior cruciate ligament (ACL) injuries occur each year in the United States. Recent studies have pointed out a correlation between the curvature of the femur intercondylar notch and the risk of noncontact ACL injury. Although several magnetic resonance (MR) imaging-based ACL diagnostics methods have already been proposed in the literature, most of them are based on machine learning or deep learning strategies, which are computationally expensive. In this paper, we propose a diagnostics framework for the risk of injury in the ACL based on the application of the inner-distance shape context (IDSC) to describe the curvature of the intercondylar notch from MR images. First, the contours of the intercondylar notch curvature from 91 MR images of the distal end of the femur (70 healthy and 21 with confirmed ACL injury) were extracted manually using standard image processing tools. Next, the IDSC was applied to calculate the similarity factor between the extracted contours and reference standard curvatures. Finally, probability density functions of the similarity factor data were obtained through parametric statistical inference, and the accuracy of the ACL injury risk diagnostics framework was assessed using receiver operating characteristic analysis (ROC). The overall results for the area under the curve (AUC) showed that the method reached a maximum accuracy of about 66%. Furthermore, the sensitivity and specificity results showed that an optimum discrimination threshold value for the similarity factor can be pursued that minimizes the incidence of false positives and false negatives simultaneously.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleDiagnostic of Injury Risk in the Anterior Cruciate Ligament Based on Shape Context Description of the Intercondylar Notch Curvature
    typeJournal Paper
    journal volume5
    journal issue2
    journal titleJournal of Engineering and Science in Medical Diagnostics and Therapy
    identifier doi10.1115/1.4053063
    journal fristpage21001-1
    journal lastpage21001-14
    page14
    treeJournal of Engineering and Science in Medical Diagnostics and Therapy:;2022:;volume( 005 ):;issue: 002
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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