Semi-automated detection of anterior cruciate ligament injury from MRI.

Journal: Computer methods and programs in biomedicine
Published Date: Dec 15, 2016

Abstract

BACKGROUND AND OBJECTIVES: A radiologist's work in detecting various injuries or pathologies from radiological scans can be tiresome, time consuming and prone to errors. The field of computer-aided diagnosis aims to reduce these factors by introducing a level of automation in the process. In this paper, we deal with the problem of detecting the presence of anterior cruciate ligament (ACL) injury in a human knee. We examine the possibility of aiding the diagnosis process by building a decision-support model for detecting the presence of milder ACL injuries (not requiring operative treatment) and complete ACL ruptures (requiring operative treatment) from sagittal plane magnetic resonance (MR) volumes of human knees.

Authors

  • Ivan Štajduhar
    Faculty of Engineering, University of Rijeka, Vukovarska 58, Rijeka, Croatia; Faculty of Engineering and Natural Sciences, Sabanci University, Üniversite Cd. No:27, Tuzla, Istanbul, Turkey. Electronic address: istajduh@riteh.hr.
  • Mihaela Mamula
    Clinical Hospital Centre Rijeka, University of Rijeka, Krešimirova 42, Rijeka, Croatia.
  • Damir Miletić
    Clinical Hospital Centre Rijeka, University of Rijeka, Krešimirova 42, Rijeka, Croatia.
  • Gözde Ünal
    Istanbul Technical University, Department of Computer Engineering, Maslak, Sarıyer, Istanbul, Turkey.

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