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      Automated computation of radiographic parameters of distal radial metaphyseal fractures in forearm X-rays.

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          Abstract

          Radiographic parameters (RPs) provide objective support for effective decision making in determining clinical treatment of distal radius fractures (DRFs). This paper presents a novel automatic RP computation pipeline for computing the six anatomical RPs associated with DRFs in anteroposterior (AP) and lateral (LAT) forearm radiographs.

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          Author and article information

          Journal
          Journal ID (iso-abbrev): Int J Comput Assist Radiol Surg
          Title: International journal of computer assisted radiology and surgery
          Publisher: Springer Science and Business Media LLC
          ISSN (Electronic): 1861-6429
          ISSN (Print): 1861-6410
          Publication date (Electronic): Dec 2023
          Volume: 18
          Issue: 12
          Affiliations
          [1 ] School of Computer Science and Engineering, The Hebrew University of Jerusalem, Israel, Edmond J. Safra Campus, Givat Ram, 9190401, Jerusalem, Israel.
          [2 ] Department of Orthopedics, Hadassah University Medical Center, Jerusalem, Israel.
          [3 ] School of Computer Science and Engineering, The Hebrew University of Jerusalem, Israel, Edmond J. Safra Campus, Givat Ram, 9190401, Jerusalem, Israel. josko@cs.huji.ac.il.
          Article
          Publisher Item ID: 10.1007/s11548-023-02907-0
          DOI: 10.1007/s11548-023-02907-0
          PubMed ID: 37097517
          SO-VID: 195a193b-76d1-4a17-9e9f-6ef004a75171
          History

          Keywords: Radiographic parameters,Distal radius fracture,Deep learning,X-ray images,Surgical decision support
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          Keywords: Radiographic parameters, Distal radius fracture, Deep learning, X-ray images, Surgical decision support

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