The Laplacian of Gaussian and arbitrary z-crossings approach applied to automated single particle reconstruction.

The automation of single particle selection and tomographic segmentation of asymmetric particles and objects is facilitated by continuing improvement of methods based on the detection of pixel discontinuity. Here, we present the new arbitrary z-crossings approach which can be employed to enhance the accuracy of edge detection algorithms that are based on the second derivative. This is demonstrated using the Laplacian of Gaussian (LoG) filter. In its normal implementation the LoG filter uses a z value of zero to define edge contours. In contrast, the arbitrary z-crossings approach allows the user to adjust z, which causes the subsequently generated contours to tend towards lighter or darker image objects, depending on the sign of z. This functionality has been coupled with an additional feature: the ability to use the major and minor axes of bounding contours to hone automated object selection. In combination, these features significantly enhance the accuracy of particle selection and the speed of tomographic segmentation. Both features have been incorporated into the software package Swarm(PS) in which parameters are automatically adjusted based on user defined target selection.