Elekta Software, Treatment Planning Systems, Maryland Heights, MO 63043, USA.
Med Phys. 2012 May;39(5):2649-58. doi: 10.1118/1.3702467.
To accurately reconstruct, and interactively reshape 3D anatomy structures' surfaces using small numbers of 2D contours drawn in the most visually informative views of 3D imagery. The innovation of this program is that the number of 2D contours can be very much smaller than the number of transverse sections, even for anatomy structures spanning many sections. This program can edit 3D structures from prior segmentations, including those from autosegmentation programs. The reconstruction and surface editing works with any image modality.
Structures are represented by variational implicit surfaces defined by weighted sums of radial basis functions (RBFs). Such surfaces are smooth, continuous, and closed and can be reconstructed with RBFs optimally located to efficiently capture shape in any combination of transverse (T), sagittal (S), and coronal (C) views. The accuracy of implicit surface reconstructions was measured by comparisons with the corresponding expert-contoured surfaces in 103 prostate cancer radiotherapy plans. Editing a pre-existing surface is done by overdrawing its profiles in image views spanning the affected part of the structure, deleting an appropriate set of prior RBFs, and merging the remainder with the new edit contour RBFs. Two methods were devised to identify RBFs to be deleted based only on the geometry of the initial surface and the locations of the new RBFs.
Expert-contoured surfaces were compared with implicit surfaces reconstructed from them over varying numbers and combinations of T/S/C planes. Studies revealed that surface-surface agreement increases monotonically with increasing RBF-sample density, and that the rate of increase declines over the same range. These trends were observed for all surface agreement metrics and for all the organs studied-prostate, bladder, and rectum. In addition, S and C contours may convey more shape information than T views for CT studies in which the axial slice thickness is greater than the pixel size. Surface editing accuracy likewise improves with larger sampling densities, and the rate of improvement similarly declines over the same conditions.
Implicit surfaces based on RBFs are accurate representations of anatomic structures and can be interactively generated or modified to correct segmentation errors. The number of input contours is typically smaller than the number of T contours spanned by the structure.
使用在三维图像的最具视觉信息量的视图中绘制的少量二维轮廓，准确地重建和交互重塑三维解剖结构的表面。本程序的创新之处在于，即使对于跨越多个截面的解剖结构，二维轮廓的数量也可以远小于横截面试图的数量。该程序可以编辑来自先前分割的三维结构，包括来自自动分割程序的分割。重建和表面编辑适用于任何成像模式。
结构由通过加权和的径向基函数 (RBF) 定义的变分隐式表面表示。这种表面是光滑的、连续的和封闭的，可以使用最优放置的 RBF 来重建，以有效地捕捉任何组合的横切（T）、矢状（S）和冠状（C）视图中的形状。通过将与 103 例前列腺癌放射治疗计划中的相应专家轮廓表面进行比较来测量隐式表面重建的准确性。对现有表面的编辑是通过在跨越结构受影响部分的图像视图中重叠其轮廓来完成的，删除适当的一组先前的 RBF，并将其余部分与新的编辑轮廓 RBF 合并。设计了两种方法来仅根据初始表面的几何形状和新 RBF 的位置来识别要删除的 RBF。
将专家轮廓表面与从其重建的隐式表面进行了比较，这些表面的 RBF 数量和 T/S/C 平面的组合各不相同。研究表明，随着 RBF 样本密度的增加，表面-表面一致性单调增加，并且在相同范围内增加率下降。这些趋势适用于所有表面一致性指标和所有研究的器官 - 前列腺、膀胱和直肠。此外，对于轴向切片厚度大于像素大小的 CT 研究，S 和 C 轮廓可能比 T 视图传达更多的形状信息。表面编辑精度也随着更大的采样密度而提高，并且在相同条件下改进率也类似地下降。
基于 RBF 的隐式表面是解剖结构的准确表示，可以交互生成或修改以纠正分割错误。输入轮廓的数量通常小于结构跨越的 T 轮廓数量。
