Paper
4 April 2016 Development and comparison of projection and image space 3D nodule insertion techniques
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Abstract
This study aimed to develop and compare two methods of inserting computerized virtual lesions into CT datasets. 24 physical (synthetic) nodules of three sizes and four morphologies were inserted into an anthropomorphic chest phantom (LUNGMAN, KYOTO KAGAKU). The phantom was scanned (Somatom Definition Flash, Siemens Healthcare) with and without nodules present, and images were reconstructed with filtered back projection and iterative reconstruction (SAFIRE) at 0.6 mm slice thickness using a standard thoracic CT protocol at multiple dose settings. Virtual 3D CAD models based on the physical nodules were virtually inserted (accounting for the system MTF) into the nodule-free CT data using two techniques. These techniques include projection-based and image-based insertion. Nodule volumes were estimated using a commercial segmentation tool (iNtuition, TeraRecon, Inc.). Differences were tested using paired t-tests and R2 goodness of fit between the virtually and physically inserted nodules. Both insertion techniques resulted in nodule volumes very similar to the real nodules (<3% difference) and in most cases the differences were not statistically significant. Also, R2 values were all <0.97 for both insertion techniques. These data imply that these techniques can confidently be used as a means of inserting virtual nodules in CT datasets. These techniques can be instrumental in building hybrid CT datasets composed of patient images with virtually inserted nodules.
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Marthony Robins, Justin Solomon, Pooyan Sahbaee, and Ehsan Samei "Development and comparison of projection and image space 3D nodule insertion techniques", Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 97835X (4 April 2016); https://doi.org/10.1117/12.2216930
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Cited by 2 scholarly publications.
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KEYWORDS
Modulation transfer functions

Computed tomography

3D modeling

Imaging systems

Reconstruction algorithms

Data modeling

Solid modeling

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