Automatic human knee cartilage segmentation from 3D magnetic resonance images

IEEE Transactions on Bio-medical Engineering
Pierre DodinFrançois Abram

Abstract

This study aimed at developing a new automatic segmentation algorithm for human knee cartilage volume quantification from magnetic resonance images (MRI). Imaging was performed using a 3T scanner and a knee coil, and the exam consisted of a DESS sequence which contrasts cartilage and soft tissues including the synovial fluid. The algorithm was developed on MRI 3D images in which the bone-cartilage interface for the femur and tibia was segmented by an independent segmentation process, giving a parametric surface of the interface. Firstly, the MR images are resampled in the neighborhood of the bone surface. Secondly, by using texture analysis techniques optimized by filtering, the cartilage is discriminated as a bright and homogeneous tissue. This process of excluding soft tissues enables the detection of the external boundary of the cartilage. Thirdly, a technology based on a Bayesian decision criterion enables the automatic separation of the cartilage and synovial fluid. Finally, the cartilage volume and changes in volume for an individual between visits was assessed using the developed technology. Validation included first, for nine knee osteoarthritis patients, a comparison of the cartilage volume and changes over time betwee...Continue Reading

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Citations

Jan 12, 2011·Annals of Biomedical Engineering·Austin J RammeNicole M Grosland
Jul 28, 2013·Annals of the Rheumatic Diseases·J-P PelletierA Guermazi
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Feb 10, 2012·IEEE Transactions on Bio-medical Engineering·José G Tamez-PeñaSaara Totterman
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Aug 30, 2017·Medical & Biological Engineering & Computing·Amir FaisalKhin Wee Lai
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Aug 28, 2020·Therapeutic Advances in Musculoskeletal Disease·Afshin JamshidiJohanne Martel-Pelletier
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Nov 20, 2021·Journal of Orthopaedic Research : Official Publication of the Orthopaedic Research Society·Anthony TeoliShawn M Robbins

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