Synergy of symmetric region grow and active contour in reconstruction of a 3D rat

The general goal of this work is modeling and reconstruction of a three-dimensional (3D) rat from a series of two-dimensional (2D) images captured from an inexpensive digital camera. We proposed a hybrid segmentation method that incorporates symmetric region grow (symRG) and active contour modeling (ACM) to robustly extract regions of interest (ROIs), such as organs, spines, and vessels. symRG is employed to enhance the segmentation performance while the edge information passed from the ACM can help prevent over-segmentation. We built a component-based software platform that includes the symRG and ACM components as well as the other image enhancement, post-segmentation processing, surface rendering components allowing the user to dynamically compose a streamlined 3D rat reconstruction procedure or script. The example dataset in this paper include 284 slices of 2D rat whole-body images. Separate scripts were used to model and visualize the body, heart, lung, stomach, and head. Few user-imposed parameters were required and the whole processing, from loading series of 2D images towards 3D rendition to demonstrate the results, is within two minutes.