RATS: Rapid Automatic Tissue Segmentation in rodent brain MRI
RATS is a rapid, robust and highly accurate algorithm for the skull-stripping of the rodent brain from MRI data. To download RATS, please go to the downloads page. For questions on using the software, please visit the FAQ page. Please contact email@example.com for any other questions and feedback.
The RATS algorithm consists of two stages. First, a mathematical morphology pipeline is used to create a rough segmentation. This is used for building a graph for a LOGISMOS-based approach for final segmentation.
Evaluation on T1-weighted rat brain MRI (left) and T2-weighted mouse brain MRI (right) show that RATS is significantly more accurate than existing methods such as pulse-coupled neural networks (PCNN) and atlas-based tissue classifiers. RATS is also significantly faster than these alternative methods, with a run time under 2 minutes.
For additional details, please refer to:
Oguz I, Zhang H, Rumple A, Sonka M. RATS: Rapid Automatic Tissue Segmentation in rodent brain MRI. Journal of neuroscience methods (2014) vol. 221 pp. 175 - 182. (link)
Yin Y, Zhang X, Williams R, Wu X, Anderson D, Sonka M. LOGISMOS - Layered Optimal Graph Image Segmentation of Multiple Objects and Surfaces: cartilage segmentation in the knee joint. IEEE Transactions on Medical Imaging (2010) vol. 29 (12) pp. 2023-37. (link)
Development was supported, in part, by NIH-NIBIB R01-EB044640.