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Proceedings Paper

A 2D to 3D ultrasound image registration algorithm for robotically assisted laparoscopic radical prostatectomy
Author(s): Mehdi Esteghamatian; Stephen E. Pautler; Charles A. McKenzie; Terry M. Peters
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Paper Abstract

Robotically assisted laparoscopic radical prostatectomy (RARP) is an effective approach to resect the diseased organ, with stereoscopic views of the targeted tissue improving the dexterity of the surgeons. However, since the laparoscopic view acquires only the surface image of the tissue, the underlying distribution of the cancer within the organ is not observed, making it difficult to make informed decisions on surgical margins and sparing of neurovascular bundles. One option to address this problem is to exploit registration to integrate the laparoscopic view with images of pre-operatively acquired dynamic contrast enhanced (DCE) MRI that can demonstrate the regions of malignant tissue within the prostate. Such a view potentially allows the surgeon to visualize the location of the malignancy with respect to the surrounding neurovascular structures, permitting a tissue-sparing strategy to be formulated directly based on the observed tumour distribution. If the tumour is close to the capsule, it may be determined that the adjacent neurovascular bundle (NVB) needs to be sacrificed within the surgical margin to ensure that any erupted tumour was resected. On the other hand, if the cancer is sufficiently far from the capsule, one or both NVBs may be spared. However, in order to realize such image integration, the pre-operative image needs to be fused with the laparoscopic view of the prostate. During the initial stages of the operation, the prostate must be tracked in real time so that the pre-operative MR image remains aligned with patient coordinate system. In this study, we propose and investigate a novel 2D to 3D ultrasound image registration algorithm to track the prostate motion with an accuracy of 2.68±1.31mm.

Paper Details

Date Published: 12 March 2011
PDF: 8 pages
Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79621Z (12 March 2011); doi: 10.1117/12.878112
Show Author Affiliations
Mehdi Esteghamatian, Robarts Research Institute (Canada)
The Univ. of Western Ontario (Canada)
Stephen E. Pautler, The Univ. of Western Ontario (Canada)
Canadian Surgical Technologies & Advanced Robotics London (Canada)
Charles A. McKenzie, Robarts Research Institute (Canada)
The Univ. of Western Ontario (Canada)
Terry M. Peters, Robarts Research Institute (Canada)
The Univ. of Western Ontario (Canada)


Published in SPIE Proceedings Vol. 7962:
Medical Imaging 2011: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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