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Interpolation by directed distance morphing

机译:通过有向距离变形进行插值

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Abstract: Shape-based interpolation (SBI) is used for interpolation between binary serial slice images. Although SBI approximates the interslice geometry more accurately than traditional techniques such as linear (L) or cubic spline (CS) interpolation, SBI produces only a binary result. This paper extends SBI to interpolation of grayscale images (SBIG) using simulated 3D distance maps to produce a grayscale image volume. Results of SBIG are superior visually (sharper detail, no artificial intensities) and quantitatively to L or CS. This is particularly evident in sagittal and coronal reconstructions. Clipping artifacts due to nonoverlapping structures or rapid changes in image brightness are minimized using simulated 3D maps. However, when objects between slices do not overlap, shape-based interpolation results in compressed or nonexistent geometry in some or all of the interpolated slices. The nonoverlapping problem is described and quantified. A new interpolation algorithm, directed distance morphing, is introduced and used to address the nonoverlapping problem. !21
机译:摘要:基于形状的插值(SBI)用于二进制序列切片图像之间的插值。尽管SBI比诸如线性(L)或三次样条(CS)插值之类的传统技术更准确地估计了层间几何图形,但SBI仅产生二进制结果。本文使用模拟3D距离图将SBI扩展到灰度图像(SBIG)的插值,以生成灰度图像量。 SBIG的结果在视觉上(清晰的细节,没有人工强度)在数量上优于L或CS。这在矢状和冠状重建中尤其明显。使用模拟3D贴图可将由于非重叠结构或图像亮度的快速变化而导致的剪裁伪像降至最低。但是,当切片之间的对象不重叠时,基于形状的插值会导致部分或所有插值切片中的几何压缩或不存在。描述和量化了不重叠的问题。引入了一种新的插值算法,即定向距离变形,并将其用于解决非重叠问题。 !21

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