Completely automated estimation of prostate volume for 3-D side-fire transrectal ultrasound using shape prior approach

Lu Li; Ramakrishnan Narayanan; Steve Miller; Feimo Shen; Al B. Barqawi; E. David Crawford; Jasjit S. Suri

doi:10.1117/12.766682

3 March 2008 Completely automated estimation of prostate volume for 3-D side-fire transrectal ultrasound using shape prior approach

Lu Li, Ramakrishnan Narayanan, Steve Miller, Feimo Shen, Al B. Barqawi, E. David Crawford, Jasjit S. Suri

Author Affiliations +

Proceedings Volume 6812, Image Processing: Algorithms and Systems VI; 68120G (2008) https://doi.org/10.1117/12.766682
Event: Electronic Imaging, 2008, San Jose, California, United States

Abstract

Real-time knowledge of capsule volume of an organ provides a valuable clinical tool for 3D biopsy applications. It is challenging to estimate this capsule volume in real-time due to the presence of speckles, shadow artifacts, partial volume effect and patient motion during image scans, which are all inherent in medical ultrasound imaging. The volumetric ultrasound prostate images are sliced in a rotational manner every three degrees. The automated segmentation method employs a shape model, which is obtained from training data, to delineate the middle slices of volumetric prostate images. Then a "DDC" algorithm is applied to the rest of the images with the initial contour obtained. The volume of prostate is estimated with the segmentation results. Our database consists of 36 prostate volumes which are acquired using a Philips ultrasound machine using a Side-fire transrectal ultrasound (TRUS) probe. We compare our automated method with the semi-automated approach. The mean volumes using the semi-automated and complete automated techniques were 35.16 cc and 34.86 cc, with the error of 7.3% and 7.6% compared to the volume obtained by the human estimated boundary (ideal boundary), respectively. The overall system, which was developed using Microsoft Visual C++, is real-time and accurate.

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Lu Li, Ramakrishnan Narayanan, Steve Miller, Feimo Shen, Al B. Barqawi, E. David Crawford, and Jasjit S. Suri "Completely automated estimation of prostate volume for 3-D side-fire transrectal ultrasound using shape prior approach", Proc. SPIE 6812, Image Processing: Algorithms and Systems VI, 68120G (3 March 2008); https://doi.org/10.1117/12.766682

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KEYWORDS

Prostate

Image segmentation

Ultrasonography

Image processing algorithms and systems

Data modeling

3D acquisition

3D image processing

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