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Prostate segmentation in 2D ultrasound images using image warping and ellipse fitting.
- Source :
-
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention [Med Image Comput Comput Assist Interv] 2006; Vol. 9 (Pt 2), pp. 17-24. - Publication Year :
- 2006
-
Abstract
- This paper presents a new algorithm for the semi-automatic segmentation of the prostate from B-mode trans-rectal ultrasound (TRUS) images. The segmentation algorithm first uses image warping to make the prostate shape elliptical. Measurement points along the prostate boundary, obtained from an edge-detector, are then used to find the best elliptical fit to the warped prostate. The final segmentation result is obtained by applying a reverse warping algorithm to the elliptical fit. This algorithm was validated using manual segmentation by an expert observer on 17 midgland, pre-operative, TRUS images. Distance-based metrics between the manual and semi-automatic contours showed a mean absolute difference of 0.67 +/- 0.18 mm, which is significantly lower than inter-observer variability. Area-based metrics showed an average sensitivity greater than 97% and average accuracy greater than 93%. The proposed algorithm was almost two times faster than manual segmentation and has potential for real-time applications.
- Subjects :
- Humans
Male
Models, Biological
Reproducibility of Results
Sensitivity and Specificity
Algorithms
Artificial Intelligence
Image Enhancement methods
Image Interpretation, Computer-Assisted methods
Pattern Recognition, Automated methods
Prostate diagnostic imaging
Prostatic Neoplasms diagnostic imaging
Ultrasonography methods
Subjects
Details
- Language :
- English
- Volume :
- 9
- Issue :
- Pt 2
- Database :
- MEDLINE
- Journal :
- Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
- Publication Type :
- Academic Journal
- Accession number :
- 17354751
- Full Text :
- https://doi.org/10.1007/11866763_3