Yunyan Ding: Efficient Mouse Brain Image Processing Using Collaborative Data Workflows on Texera

In the field of neuroscience, accurately mapping the complex three-dimensional (3D) neural circuitry and architecture of the brain is crucial for advancing our understanding of brain functions and disorders. In this study, we introduce a distributed computational pipeline designed for processing high-resolution mouse brain tile images captured by TissueCyte. This pipeline efficiently and accurately stitches these tiles and stacks 2D sections to construct detailed whole mouse brain models in 3D. Our high-quality 3D volumes can facilitate secondary analyses such as whole-brain 3-dimensional registration and segmentation, cell counting, and high-resolution volumetric visualization. By utilizing specialized optimization methods within Texera platform to distribute computational resources, our pipeline achieves an over 80\% reduction in processing times, enhancing the efficiency significantly. Additionally, this pipeline is designed with scalability and flexibility, enabling it to process large volumes of high-resolution neuroimaging data across various computational environments. Our work is developed through a collaborative effort among neuroscience, computer vision, and data processing teams, exemplifying the power of creating tools for interdisciplinary collaboration in addressing complex research challenges.

Yunyan Ding is a second-year Ph.D. student in the Computer Science Department at UC Irvine. Her research interests include data processing systems and big data analytics.