Back to Search
Start Over
An automatic segmentation method for regional analysis of femoral neck images acquired by pQCT.
- Source :
-
Annals of biomedical engineering [Ann Biomed Eng] 2011 Jan; Vol. 39 (1), pp. 172-84. Date of Electronic Publication: 2010 Sep 08. - Publication Year :
- 2011
-
Abstract
- We developed an automatic method for regional analysis of femoral neck images acquired by peripheral quantitative computed tomography (pQCT), based on automatic spatial re-alignment and segmentation; the segmentation method, based on a morphological approach, explicitly accounts for the presence of three different bone compartments: cortical region, trabecular region, and transition zone between cortical and trabecular compartments. The proposed method was applied on 13 femoral neck sections derived from female donors who were undergoing hip replacement surgery for primary degenerative arthritis or fracture, and a typical densitometric and structural analysis was performed both globally and regionally. The proposed segmentation method was quantitatively evaluated by comparing automatic contour and the corresponding manual contours delineated by three operators using metrics based on surface distance (average symmetric distance, ASD) and volumetric overlapping (dice similarity coefficient, DSC). The same approach was used to validate the automatic spatial orientation, considering as metric the difference between manual and automatic angle orientation. Results confirm a satisfactory agreement between automatic and manual performances (ASD < 0.41 mm, DSC > 0.91, orientation difference = 3.61°) and show that globally our algorithm performs very well. Concerning regional analysis application, from our results we can observe that significant differences are present among the four bone quadrants.
- Subjects :
- Aged
Aged, 80 and over
Female
Humans
Radiographic Image Enhancement methods
Reproducibility of Results
Sensitivity and Specificity
Algorithms
Artificial Intelligence
Femur Neck diagnostic imaging
Pattern Recognition, Automated methods
Radiographic Image Interpretation, Computer-Assisted methods
Subjects
Details
- Language :
- English
- ISSN :
- 1573-9686
- Volume :
- 39
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Annals of biomedical engineering
- Publication Type :
- Academic Journal
- Accession number :
- 20824341
- Full Text :
- https://doi.org/10.1007/s10439-010-0154-8