Medical imaging from CT and MRI scans has become essential to clinicians for diagnosis, treatment planning and even prevention of a wide array of conditions. The presentation of image data volumes as 2D slice series provides some challenges with visualising internal structures. 3D reconstructions of organs and other tissue samples from data with low scan resolution leads to a ‘stepped’ appearance. This paper demonstrates how to improve 3D visualisation of features and automated preparation for 3D printing from such low resolution data, using novel techniques for morphing from one slice to the next. The boundary of the starting contour is grown until it matches the boundary of the ending contour by adapting a variant of the Fast Marching Method (FMM). Our spoke based approach generates scalar speed field for FMM by estimating distances to boundaries with line segments connecting the two boundaries. These can be regularly spaced radial spokes or spokes at radial extrema. We introduce clamped FMM by running the algorithm outwards from the smaller boundary and inwards from the larger boundary and combining the two runs to achieve FMM growth stability near the two region boundaries. Our method inserts a series of uniformly distributed intermediate contours between each pair of consecutive slices from the scan volume thus creating smoother feature boundaries. Whilst hard to quantify, our overall results give clinicians an evidently improved tangible and tactile representation of the tissues, that they can examine more easily and even handle.
Samuel Littley and Irina Voiculescu, "Interpolation of 3D slice volume data for 3D printing," Proc. SPIE 10135, Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, 101351E (Presented at SPIE Medical Imaging: February 16, 2017; Published: 3 March 2017); https://doi.org/10.1117/12.2254616.
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