The goal is for the candidate to embark on a career transformation by acquiring critical knowledge and skills in biomedical sciences and become a productive and successful investigator in emerging biomedical areas with a unique set of expertises. One of the important components consists of projects in genetic phenotyping of small animals using in vivo bioimaging. The research will first tackle the technically easier problem of measuring and analyzing regional fat distribution in mice so as to identify potential subgroups with specific health problems; e.g., increased levels of visceral fat have been associated with insulin resistance, cardiovascular disease, and other metabolic syndromes. Building on this experience, the project will proceed to the identification of skeletal phenotypes using 3D micro-CT imaging. Not only will image segmentation be a challenge, a paradigm for extracting complex anatomical information will be created, as for example from a mouse skeleton, and clustering data into phenotypes for comparison with genotypes. This paradigm will set a standard and open new possibilities in deriving biomedical knowledge from mouse models.
| Huang, Fangping; Narayan, Sreenath; Wilson, David et al. (2011) A fast iterated conditional modes algorithm for water-fat decomposition in MRI. IEEE Trans Med Imaging 30:1480-92 |
| Narayan, Sreenath; Huang, Fangping; Johnson, David et al. (2011) Fast lipid and water levels by extraction with spatial smoothing (FLAWLESS): three-dimensional volume fat/water separation at 7 Tesla. J Magn Reson Imaging 33:1464-73 |
| Szymanski, Jacek; Wilson, David L; Zhang, Guo-Qiang (2009) MIMI: multimodality, multiresource, information integration environment for biomedical core facilities. J Digit Imaging 22:535-47 |
