Does pixel/voxel-size limit the measurement of distances in CBCT-tomography?

Abstract

The necessity to obtain relevant structural information from tomographic images is an all-pervasive step in a host of clinical and research-areas. Cone Beam Computed Tomography (CBCT) is the imaging modality often used among the many available.Currently approaches to extract structural properties from raw CBCT-images, involve some manual intervention by experts to measure their properties, such as size and displacements of their geometrical structures. Regarding the factors limiting the precision of these measurements, such as voxel-size and image contrast, we find conflicting statements in the literature. It is therefore useful to provide accurate data under well-defined experimental conditions.Here we present a method and associated software to measure displacements of geometrical structures. We also determined the minimum measureable displacement and minimum detectable defect in terms of voxel size. We select as our geometrical structure a sample of bovine bone and to provide a set of defects, we drilled a pattern of holes into it. We determined the hole's three-dimensional structures using confocal spectroscopy.In order to obtain the minimum measurable displacement, we acquired CBCT-tomographies containing a stationary reference and micro-metrically cnc controlled displacements of the sample. We then process these images with our software to extract the distances and compare them with the cnc displacements. All our processing includes a computational interpolation from the voxel-size of 0.35 mm corresponding to our CBCT-tomographies, down to 0.05 mm. We find that sample-displacements can be measured with a precision of ∼ 20µ, 17 times smaller than the voxel-size of 0.35 mm.To measure the size of the holes using our CBCT-tomographies, we first register the 1 holes onto a hole-free region of the sample with our software, then overlay the result 2 with the three-dimensional structure obtained from confocal spectroscopy. We find the 3 minimum detectable hole-size to be 0.7 mm, twice the voxel-size. 4 PLOS 1/9 Hole characterization 76 In order to infer the size of the smallest holes, which we can detect using tomographic 77 images processed by our algorithm, we need a precise enough measure of their spatial 78 geometry. We therefore used confocal microscopy [21] (Lext 3D Laser Measuring, 79 Center Valley, PA, USA) using laser wavelength of 405nm to obtain the 80 three-dimensional structure of the holes. This technique uses a laser to produce 81 PLOS 3/9 110We segment the volumetric image of the whole setup Fig.(1 B), using the region 111 competition algorithm [22] implemented in the ITK-SNAP segmentation software [23], 112 before and after displacement to extract the regions of interest: bone sample, circular 113 dish and rod. Yet the borders of the bone sample, which will be used to measure 114 displacements, are not always well defined. To refine their positions, we expand the 115 region labeled bone sample via a level set contour propagation [24] followed by an AND 116 operation between the bone sample region b...