Prostate segmentation in 2d ultrasound images using image warping and ellipse fitting

Authors:
Sara Badiei;Septimiu E. Salcudean;Jim Varah;W. James Morris
Affiliations:
Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada;Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada;Department of Computer Science, University of British Columbia, Vancouver;Vancouver Cancer Center, British Columbia Cancer Agency, Vancouver
Venue:
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Year:
2006

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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 ± 0.18mm, 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.