Computational NeuroscienceAn automatic rat brain extraction method based on a deformable surface model

- We developed an automatic rat brain extraction algorithm, called the Rat Brain Deformable model method (RBD).
- RBD is based on the deformable surface model.
- RBD outperformed the existing rat brain extraction methods.
- RBD achieved a higher accuracy of >92% volume overlap for brain extraction.
- RBD was also robust against signal inhomogeneity in the images.

The extraction of the brain from the skull in medical images is a necessary first step before image registration or segmentation. While pre-clinical MR imaging studies on small animals, such as rats, are increasing, fully automatic imaging processing techniques specific to small animal studies remain lacking. In this paper, we present an automatic rat brain extraction method, the Rat Brain Deformable model method (RBD), which adapts the popular human brain extraction tool (BET) through the incorporation of information on the brain geometry and MR image characteristics of the rat brain. The robustness of the method was demonstrated on T2-weighted MR images of 64 rats and compared with other brain extraction methods (BET, PCNN, PCNN-3D). The results demonstrate that RBD reliably extracts the rat brain with high accuracy (>92% volume overlap) and is robust against signal inhomogeneity in the images.