Data for: Artificial squares, rectangles and Xray images in random rotational orientations, centered and in different sizes

SORFAC-CT (Cylindrical-Topology Self-Organizing Reference-Free Alignment and Classification; pronounced sôr-fakt or sôr-fak-si-ti) is an efficient method of reference-free rotational image alignment. SORFAC-CT circumvents the dependence of subjective user- or computer-generated external or internal reference images used by other reference-based techniques. Alignment is performed using a Kohonen self-organizing map (SOM), configured on a cylindrical array of artificial neurons. Although alternative alignment protocols often depend on an expert to adjust many ad hoc parameters, SORFAC-CT instead achieves the minimization of one objectively calculated target function by varying only two free parameters. Because SOMs preserve the topological properties of the training (dataset) images, the relative in-plane rotational orientations of dataset images are obtained directly from the array’s intrinsic cylindrical coordinate system by noting each mapped dataset image’s respective azimuthal angle ..., As explained in the Materials and Methods, these datasets were generated using IMAGIC software. , SORFAC or SORFAC-CT may be used on these three sets of test images. The full-featured software is freely available upon request to the author, and the source code is available too.Â