Development of a Hausdorff distance based 3D quantification technique to evaluate the CT imaging system impact on depiction of lesion morphology

Pooyan Sahbaee; Marthony Robins; Justin Solomon; Ehsan Samei

doi:10.1117/12.2216503

4 April 2016 Development of a Hausdorff distance based 3D quantification technique to evaluate the CT imaging system impact on depiction of lesion morphology

Pooyan Sahbaee, Marthony Robins, Justin Solomon, Ehsan Samei

Author Affiliations +

Proceedings Volume 9783, Medical Imaging 2016: Physics of Medical Imaging; 97835V (2016) https://doi.org/10.1117/12.2216503
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

The purpose of this study was to develop a 3D quantification technique to assess the impact of imaging system on depiction of lesion morphology. Regional Hausdorff Distance (RHD) was computed from two 3D volumes: virtual mesh models of synthetic nodules or “virtual nodules” and CT images of physical nodules or “physical nodules”. The method can be described in following steps. First, the synthetic nodule was inserted into anthropomorphic Kyoto thorax phantom and scanned in a Siemens scanner (Flash). Then, nodule was segmented from the image. Second, in order to match the orientation of the nodule, the digital models of the “virtual” and “physical” nodules were both geometrically translated to the origin. Then, the “physical” was gradually rotated at incremental 10 degrees. Third, the Hausdorff Distance was calculated from each pair of “virtual” and “physical” nodules. The minimum HD value represented the most matching pair. Finally, the 3D RHD map and the distribution of RHD were computed for the matched pair. The technique was scalarized using the FWHM of the RHD distribution. The analysis was conducted for various shapes (spherical, lobular, elliptical, and speculated) of nodules. The calculated FWHM values of RHD distribution for the 8-mm spherical, lobular, elliptical, and speculated “virtual” and “physical” nodules were 0.23, 0.42, 0.33, and 0.49, respectively.

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Pooyan Sahbaee, Marthony Robins, Justin Solomon, and Ehsan Samei "Development of a Hausdorff distance based 3D quantification technique to evaluate the CT imaging system impact on depiction of lesion morphology", Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 97835V (4 April 2016); https://doi.org/10.1117/12.2216503

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KEYWORDS

Image segmentation

3D image processing

Computed tomography

3D modeling

Imaging systems

Spherical lenses

Distance measurement

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