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Proceedings Paper

Deformable registration for integration of MRI/MRSI information in TRUS-guided prostate biopsy
Author(s): Wei Shao; Ruoyun Wu; Choon Hua Thng; Keck Voon Ling; Henry Sun Sien Ho; Christopher Wai Sam Cheng; Wan Sing Ng
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Paper Abstract

Prostate cancer has been ranked as the second leading cause of cancer death in men. The existence of cancer in prostate is usually examined by a biopsy procedure under the transrectal ultrasound (TRUS) guidance. Development of a prostate biopsy robotics can alleviate urologists' labor and guarantee accuracy. However, it is usually impossible to identify cancer region in the noisy ultrasound images, thus leading to a random biopsy protocol for prostate. It is being recognized that Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy Imaging (MRSI) techniques are potential to diagnose cancer distribution in prostate. So navigating the biopsy needle towards those cancer-suspected sites could improve the cancer detection rate and reduce the possibility of false negative diagnosis results. As the prostate usually deforms under the different rectal filling of probes and change of patient postures, a deformable registration scheme is implemented for the integration of the pre-operative MRI/MRSI information with the intra-operative TRUS images. A framework including a global rigid alignment and a sequent non-rigid transformation was described in this paper to match the cross-modal prostate surfaces and thereafter their volumes. For validation, an elastic prostate phantom that simulated the human condition was built up, with fiducial markers implanted inside the phantom prostate as the "ground truth". It shows that our method can achieve at least 30% improvement in accuracy compared with an affine transformation. Preliminary study was also conducted on patient data but with visual assessments presented only due to the current lack of "ground truth".

Paper Details

Date Published: 29 April 2005
PDF: 11 pages
Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.594897
Show Author Affiliations
Wei Shao, Nanyang Technological Univ. (Singapore)
Ruoyun Wu, Nanyang Technological Univ. (Singapore)
Choon Hua Thng, National Cancer Ctr. (Singapore)
Keck Voon Ling, Nanyang Technological Univ. (Singapore)
Henry Sun Sien Ho, Singapore General Hospital (Singapore)
Christopher Wai Sam Cheng, Singapore General Hospital (Singapore)
Wan Sing Ng, Nanyang Technological Univ. (Singapore)


Published in SPIE Proceedings Vol. 5747:
Medical Imaging 2005: Image Processing
J. Michael Fitzpatrick; Joseph M. Reinhardt, Editor(s)

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