Feature sensitive surface extraction from volume data
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
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Medical diagnostics necessitates performing quantitative analysis and measurements of 2D or 3D data. The length, angle, region area, 3D surface area, and volume are measured to determine medical parameters. This paper presents an uncertainty estimation for a 3D surface model created from object boundaries using CT, MRI series of images. Next, thirty dry bone pelvises underwent the morphological, classical radiological and CT tests, and were reconstructed in 3D. Then, the obtained results for selected parameters describing the pelvis and the orientation of coxal acetabulum were compared. Using dray human pelvises for validation study is extremely important to convince physicians that measurements results based on virtual models are comparable to the same results obtained in the classical way.