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Accurate Techniques of Thickness and Volume Measurement of Cartilage from Knee Joint MRI Using Semiautomatic Segmentation Methods

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • Mallikarjunaswamy M. S.

    (Sri Jayachamarajendra College of Engineering, JSS Science and Technology University, Department of Electronics and Instrumentation Engineering)

  • Mallikarjun S. Holi

    (University B.D.T. College of Engineering, Constituent College of VTU, Belagavi)

  • Rajesh Raman

    (J. S. S. Medical College and Hospital, JSS Academy of Higher Education and Research, Department of Radio-Diagnosis)

  • J. S. Sujana Theja

    (J. S. S. Medical College and Hospital, JSS Academy of Higher Education and Research, Department of Orthopedics)

Abstract

Accurate quantification of cartilage is useful for diagnosis and treatment of osteoarthritis (OA) affected knee joints. Image processing techniques are required for clear visualization and quantification of cartilage degradations in different regions in OA affected knee joints. In this work femur articular cartilage were segmented from MRI of knee joint using two semiautomatic methods namely canny edge detection based method and radial search based method. The thickness and volume of cartilage were measured region wise using segmented images. The cartilages were also segmented using standard method under the supervision of radiologists for comparison and to find the accuracy of quantification results of two semiautomatic methods. The results of measurements using semiautomatic segmentation methods shown good accuracy and the errors are limited to less than 5%.

Suggested Citation

  • Mallikarjunaswamy M. S. & Mallikarjun S. Holi & Rajesh Raman & J. S. Sujana Theja, 2020. "Accurate Techniques of Thickness and Volume Measurement of Cartilage from Knee Joint MRI Using Semiautomatic Segmentation Methods," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 1017-1025, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_103
    DOI: 10.1007/978-3-030-41862-5_103
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