Advances in 3-D imaging and tissue clearing  - a class of methods to make extracted organs physically transparent for analysis - are responsible for generating vast amounts of data, with single cleared organs reaching hundreds of gigabytes. In a project led by Alon Greenbaum and Ken Chan in Viviana Gradinaru's lab at Caltech, they extended these methods to work on hard, opaque bones, so that single bones could be imaged in 3-D to interrogate the cells inside. We provided computational assistance via scripting, image processing, and machine learning techniques to automate and aid in image analysis, cell counting, and statistical analysis.

In particular, we work on the following:

• Automated pipelines for manipulating large bone image files to accommodate:

• Stitching using Terastitcher

• Image processing using Matlab

• Visualization using Imaris

• Automated cell counting using image statistics and neural network classification

• Simulations of stereology experiments to validate the benefits of 3D imaging

• Cell counting and defining regions of interest