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Automated analysis of hip joint cartilage combining MR T2 and three-dimensional fast-spin-echo images.
- Source :
-
Magnetic resonance in medicine [Magn Reson Med] 2016 Jan; Vol. 75 (1), pp. 403-13. Date of Electronic Publication: 2015 Jan 30. - Publication Year :
- 2016
-
Abstract
- Purpose: To validate a fully automated scheme to extract biochemical information from the hip joint cartilages using MR T2 mapping images incorporating segmentation of co-registered three-dimensional Fast-Spin-Echo (3D-SPACE) images.<br />Methods: Manual analyses of unilateral hip (3 Tesla) MR images of 24 asymptomatic volunteers were used to validate a 3D deformable model method for automated cartilage segmentation of SPACE scans, partitioning of the individual femoral and acetabular cartilage plates into clinically defined sub-regions and propagating these results to T2 maps to calculate region-wise T2 value statistics. Analyses were completed on a desktop computer (∼ 10 min per case).<br />Results: The mean voxel overlap between automated A and manual M segmentations of the cartilage volumes in the (clinically based) SPACE images was 73% (100 × 2|A∩M|/[|A|+|M|]). The automated and manual analyses demonstrated a relative difference error <10% in the median "T2 average signal" for each cartilage plate. The automated and manual analyses showed consistent patterns between significant differences in T2 data across the hip cartilage sub-regions.<br />Conclusion: The good agreement between the manual and automatic analyses of T2 values indicates the use of structural 3D-SPACE MR images with the proposed method provides a promising approach for automated quantitative T2 assessment of hip joint cartilages.<br /> (© 2015 Wiley Periodicals, Inc.)
- Subjects :
- Adult
Algorithms
Female
Humans
Image Enhancement methods
Male
Reproducibility of Results
Sensitivity and Specificity
Subtraction Technique
Young Adult
Cartilage, Articular anatomy & histology
Echo-Planar Imaging methods
Hip Joint anatomy & histology
Image Interpretation, Computer-Assisted methods
Imaging, Three-Dimensional methods
Pattern Recognition, Automated methods
Subjects
Details
- Language :
- English
- ISSN :
- 1522-2594
- Volume :
- 75
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Magnetic resonance in medicine
- Publication Type :
- Academic Journal
- Accession number :
- 25644241
- Full Text :
- https://doi.org/10.1002/mrm.25598