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

Mallikarjunaswamy M. S. (), Mallikarjun S. Holi, Rajesh Raman and J. S. Sujana Theja
Additional contact information
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

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 1017-1025 from Springer

Abstract: 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%.

Keywords: Knee joint; Cartilage; Magnetic resonance imaging; Semiautomatic segmentation; Osteoarthritis (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_103

Ordering information: This item can be ordered from
http://www.springer.com/9783030418625

DOI: 10.1007/978-3-030-41862-5_103

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().