Affiliations 

  • 1 Centre for Intelligent Signal and Imaging Research, Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Tronoh, Perak 31750, Malaysia
  • 2 Centre for Intelligent Signal and Imaging Research, Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Tronoh, Perak 31750, Malaysia. Electronic address: dileep.kumar@petronas.com.my
  • 3 Department of Rheumatology, Pantai Hospital Ipoh, Ipoh, Perak, Malaysia
  • 4 Imaging Department, Pantai Hospital Ipoh, Ipoh, Perak, Malaysia
Acad Radiol, 2015 Jan;22(1):93-104.
PMID: 25481518 DOI: 10.1016/j.acra.2014.08.008

Abstract

Quantitative assessment of knee articular cartilage (AC) morphology using magnetic resonance (MR) imaging requires an accurate segmentation and 3D reconstruction. However, automatic AC segmentation and 3D reconstruction from hydrogen-based MR images alone is challenging because of inhomogeneous intensities, shape irregularity, and low contrast existing in the cartilage region. Thus, the objective of this research was to provide an insight into morphologic assessment of AC using multilevel data processing of multinuclear ((23)Na and (1)H) MR knee images.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.