TY  - CHAP
AV  - none
SN  - 978-1-4673-2585-1
SP  - 55
KW  - High performance computing; MRI; cloud; computer vision; image analysis; neuroimaging; phenotyping
N2  - The combined use of mice that have genetic mutations (transgenic mouse models) of human pathology and advanced neuroimaging methods (such as MRI) has the potential to radically change how we approach disease understanding, diagnosis and treatment. Morphological changes occurring in the brain of transgenic animals as a result of the interaction between environment and genotype, can be assessed using advanced image analysis methods, an effort described as ?mouse brain phenotyping?. However, the computational methods required for the analysis of high-resolution brain images are demanding. In this paper, we propose a computationally effective cloud-based implementation of morphometric analysis of high-resolution mouse brain datasets. We show that the proposed approach is highly scalable and suited for a variety of methods for MR-based brain phenotyping. The proposed approach is easy to deploy, and could become an alternative for laboratories that may require instant access to large high performance computing infrastructure.
ID  - eprints1515
Y1  - 2012///
EP  - 60
TI  - Mouse neuroimaging phenotyping in the cloud
T2  - Proceedings of the 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA), 2012 
UR  - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6469527&isnumber=6469475
PB  - IEEE
A1  - Minervini, Massimo
A1  - Damiano, Mario
A1  - Tucci, Valter
A1  - Bifone, Angelo
A1  - Gozzi, Alessandro
A1  - Tsaftaris, Sotirios A.
ER  -