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Registration of 3D ultrasound to computed tomography images of the kidney Xiang, Jing
Abstract
The integration of 3D computed tomography (CT) and ultrasound (US) is of considerable interest because it can potentially improve many minimally invasive procedures such as robot-assisted laparoscopic partial nephrectomy. Partial nephrectomy patients often receive preoperative CT angiography for diagnosis. The 3D CT image is of high quality and has a large field of view. Intraoperatively, dynamic real-time images are acquired using ultrasound. While US is real-time and safe for frequent imaging, the images captured are noisy and only provide a limited perspective. Providing accurate registration between the two modalities would enhance navigation and image guidance for the surgeon because it can bring the pre-operative CT into a current view of the patient provided by US. The challenging aspect of this registration problem is that US and CT produce very different images. Thus, a recurring strategy is to use preprocessing techniques to highlight the similar elements between the images. The registration technique presented here goes further by dynamically simulating an US image from the CT, and registering the simulated image to the actual US. This is validated on US and CT volumes of porcine phantom data. Validation on realistic phantoms remains an ongoing problem in the development of registration methods. A detailed protocol is presented here for constructing tissue phantoms that incorporate contrast agent into the tissue such that the kidneys appear representative of in vivo human CT angiography. Registration with 3D CT is performed successfully on the reconstructed 3D US volumes, and the mean TREs ranged from 1.8 to 3.5 mm. In addition, the simulation-based algorithm was revised to consider the shape of the US beam by using pre-scan converted US data. The corresponding CT image is iteratively interpolated along the direction of the US beam during simulation. The mean TREs resulting from registering the pre-scan US data and CT data were between 1.4 to 2.6 mm. The results show that both methods yield similar results and are promising for clinical application. Finally, the method is tested on a set of in vivo CT and US images of a partial nephrectomy patient, and the registration results are discussed.
Item Metadata
Title |
Registration of 3D ultrasound to computed tomography images of the kidney
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2010
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Description |
The integration of 3D computed tomography (CT) and ultrasound (US) is
of considerable interest because it can potentially improve many minimally
invasive procedures such as robot-assisted laparoscopic partial nephrectomy.
Partial nephrectomy patients often receive preoperative CT angiography for
diagnosis. The 3D CT image is of high quality and has a large field of view.
Intraoperatively, dynamic real-time images are acquired using ultrasound.
While US is real-time and safe for frequent imaging, the images captured are
noisy and only provide a limited perspective. Providing accurate registration
between the two modalities would enhance navigation and image guidance
for the surgeon because it can bring the pre-operative CT into a current
view of the patient provided by US.
The challenging aspect of this registration problem is that US and CT
produce very different images. Thus, a recurring strategy is to use preprocessing techniques to highlight the similar elements between the images.
The registration technique presented here goes further by dynamically simulating an US image from the CT, and registering the simulated image to
the actual US. This is validated on US and CT volumes of porcine phantom data. Validation on realistic phantoms remains an ongoing problem in
the development of registration methods. A detailed protocol is presented
here for constructing tissue phantoms that incorporate contrast agent into
the tissue such that the kidneys appear representative of in vivo human
CT angiography. Registration with 3D CT is performed successfully on the
reconstructed 3D US volumes, and the mean TREs ranged from 1.8 to 3.5
mm. In addition, the simulation-based algorithm was revised to consider
the shape of the US beam by using pre-scan converted US data. The corresponding CT image is iteratively interpolated along the direction of the
US beam during simulation. The mean TREs resulting from registering the
pre-scan US data and CT data were between 1.4 to 2.6 mm. The results
show that both methods yield similar results and are promising for clinical
application. Finally, the method is tested on a set of in vivo CT and US
images of a partial nephrectomy patient, and the registration results are
discussed.
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Genre | |
Type | |
Language |
eng
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Date Available |
2010-08-26
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0071184
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2010-11
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International