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Proceedings Paper

Improved validation platform for ultrasound-based monitoring of thermal ablation
Author(s): Hamed Peikari; Andras Lasso; Gabor Fichtinger
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Paper Abstract

PURPOSE: Thermal ablation is a popular method in local cancer management; however it is extremely challenging to predict thermal changes in vivo. Ultrasound could be a convenient and inexpensive imaging modality for real-time monitoring of the ablation, but the required advanced image processing algorithms need extensive validation. Our goal is to design and develop a reliable test-bed for validation of these monitoring algorithms. METHOD: We previously developed a test-bed, consisting of ablated tissue sample and fiducial lines embedded in tissue-mimicking gel.1 The gel block is imaged by ultrasound and sliced to acquire pathology images. Following fiducial localization in both image modalities, the pathology and US data were registered. Ground truth ablated region is retrieved from pathology images and compared to the result of the ultrasound-based processing in 3D space. We improved on this platform to resolve limitations that hindered its usage in a larger-scale validation study. A simulator for evaluating and optimizing different line fiducial structures was implemented, and a new fiducial line structure was proposed. RESULTS: The new proposed fiducial configuration outperforms the previous in terms of accuracy, fiducial visibility, and use of larger tissue samples. Simulation results show improvement in pose recovery accuracy using our proposed fiducial structure, reducing target registration error (TRE) by 34%. Inaccurate pixel spacing information and fiducial localization noise are the main sources of error in slice pose recovery. CONCLUSION: A new generation of test-bed was developed, with software that does not require lengthy manual data processing, and is easier to maintain and extend. Further experimental work is required to optimize phantom preparation and precise pixel spacing computation.

Paper Details

Date Published: 1 March 2011
PDF: 8 pages
Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 79641H (1 March 2011); doi: 10.1117/12.878333
Show Author Affiliations
Hamed Peikari, Queen's Univ. (Canada)
Andras Lasso, Queen's Univ. (Canada)
Gabor Fichtinger, Queen's Univ. (Canada)


Published in SPIE Proceedings Vol. 7964:
Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; David R. Holmes, Editor(s)

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