Construction of an active digital atlas of the mouse brain, with current emphasis on the brainstem. This is a full stack project that spans from data acquisition to imaging processing to computational anatomy. Involves Prof. Y. Freund in CSE, Prof. D. Kleinfeld in Physics and Neurobiology, and their professional associates.
Type of Data:
High resolution, light-level structural and functional images of the mouse brain
Approximate Data Size:
1 Tb per brain
Methods Student Openings:
Methods Student Funding:
Methods Student Prerequisites:
The candidate needs to have experience manipulating large sets of images with Python. This includes extensive use of numpy and opencv. Clean, maintainnable, and documented coding skills are a must. All work is done on Linux systems with extensive use of BASH, awk, and other command line tools. In addition, it would be useful to have skills with MySQL, Django, Typescript, and ImageMagick. For initial efforts on this project by an CSE student, see "An active texture-based digital atlas enables automated mapping of structure and markers across brains." Y. Chen, L. E. McElvain, A. Tolpygo, D. Ferrant, B. Friedman, P. P. Mitra, H. J. Karten, Y. Freund* and D. Kleinfeld*, Nature Methods (2019) 16:314-350.