Systems and methods for 3D image distification
摘要
說明書
At block 306, the computing device generates one or more two dimensional (2D) image matrices that correspond to the obtained 3D images. In one embodiment, a single, uniform 2D image matrix may be generated and used for all 3D images in the Distification method 300. Such an embodiment provides a high degree of compatibility and standardization across the 3D images to be normalized. In other embodiments, a 2D image matrix may be generated for each 3D image, for example, to provide greater control of the 3D images.
The 2D image matrix can include one or more 2D matrix points that are mapped to or are otherwise overlaid with the 3D image. Each 2D matrix point in the 2D matrix is associated with a horizontal coordinate (e.g., an x-value) and a vertical coordinate (e.g., a y-value). In certain embodiments, the 2D points of the 2D matrix can have a different level of granularity with respect to the 3D points in the 3D image. For example, a 2D matrix may be generated to include a total of 300 horizontal coordinates and 200 vertical coordinates, but a corresponding 2D-axis of the related 3D image, and for the same 2D dimensional space, may include a total of 900 horizontal coordinates and 400 vertical coordinates. In such embodiment, the two 2D surfaces would not share a one-to-one mapping with respect to the horizontal and vertical coordinates on each of the surfaces. In the current example, the 2D image matrix is said to have a more granular resolution the 2D-axis of the 3D image. Thus, in the current example, the total quantity of the 2D matrix points mapped onto the 3D image is less than the total quantity of horizontal and vertical coordinate pairs of the 3D points of the 3D image. Increasing the granularity of the 2D image matrix may increase the processing performance of the computing device because the computing device would have fewer points to analyze.
