A Proposal for Automated Analytical Method of MDCT Images for Risk Measurement of Recurrent Patellar Dislocation

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  • Maki Akira
    Department of Human and Artificial Intelligent Systems, Faculty of Engineering, University of Fukui
  • Nagamune Kouki
    Department of Human and Artificial Intelligent Systems, Graduate School of Engineering, University of Fukui
  • Oka Shinya
    Department of Orthopaedic Surgery, Graduate School of Medicine, Kobe University
  • Hoshino Yuichi
    Department of Orthopaedic Surgery, Graduate School of Medicine, Kobe University
  • Matsushita Takehiko
    Department of Orthopaedic Surgery, Graduate School of Medicine, Kobe University
  • Kubo Seiji
    Department of Orthopaedic Surgery, Graduate School of Medicine, Kobe University
  • Kuroda Ryosuke
    Department of Orthopaedic Surgery, Graduate School of Medicine, Kobe University
  • Kurosaka Masahiro
    Department of Orthopaedic Surgery, Graduate School of Medicine, Kobe University

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Other Title
  • 反復性膝蓋骨亜脱臼の危険性測定を目的としたMDCT画像の自動解析法の提案
  • ハンプクセイ シツガイコツ アダッキュウ ノ キケンセイ ソクテイ オ モクテキ ト シタ MDCT ガゾウ ノ ジドウ カイセキホウ ノ テイアン

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Currently, doctors determine a treatment way of recurrent patellar dislocation with total consideration for the knee condition by using image discrimination and/or palpation. However, the determination depends much on the doctors. It results in variations of the judgment among them. Therefore, this study aims to propose an automated evaluation method that can provide a criterion of the subluxation knee for determination of a treatment to support doctors without subjective experiences. The proposed method analyzes an abnormal degree of patellofemoral surface by calculating a femoral pose from the medial and lateral epicondyles and detecting a patellar displacement and a profile of the groove. Then, it can provide a value represents a risk of the subluxation by considering them totally.

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