论文标题
切片插补：各向异性3D医疗图像分割的中间切片插值
Slice Imputation: Intermediate Slice Interpolation for Anisotropic 3D Medical Image Segmentation
论文作者
论文摘要
我们介绍了一种基于框架插值的新型方法，用于插入切片，以提高各向异性3D医学图像的分割准确性，其中在各向异性3D医疗体积中，切片的数量及其相应的分割标签可以增加两个连续的切片之间。与以前仅着眼于轴向方向的平滑度的固定间插补方法不同，本研究旨在提高所有三个方向上插值3D医疗体积的平滑度：轴向，矢状和冠状。尤其是提出的多任务套管插补方法，尤其结合了平滑度损失函数，以评估插值3D医疗体积在整个平面方向（矢状和冠状）的平滑度。它不仅改善了插值3D医疗体积在整个面向方向上的分辨率，而且还可以将它们转化为各向同性表示，从而导致更好的分割性能。对大脑，肝肿瘤分割和前列腺分割的整个肿瘤分割的实验表明，在大多数情况下，我们的方法在计算机断层扫描和磁共振图像上都超过了竞争性的插入方法。
We introduce a novel frame-interpolation-based method for slice imputation to improve segmentation accuracy for anisotropic 3D medical images, in which the number of slices and their corresponding segmentation labels can be increased between two consecutive slices in anisotropic 3D medical volumes. Unlike previous inter-slice imputation methods, which only focus on the smoothness in the axial direction, this study aims to improve the smoothness of the interpolated 3D medical volumes in all three directions: axial, sagittal, and coronal. The proposed multitask inter-slice imputation method, in particular, incorporates a smoothness loss function to evaluate the smoothness of the interpolated 3D medical volumes in the through-plane direction (sagittal and coronal). It not only improves the resolution of the interpolated 3D medical volumes in the through-plane direction but also transforms them into isotropic representations, which leads to better segmentation performances. Experiments on whole tumor segmentation in the brain, liver tumor segmentation, and prostate segmentation indicate that our method outperforms the competing slice imputation methods on both computed tomography and magnetic resonance images volumes in most cases.
