Significance: High-throughput optical microscopy is currently transforming the research fields of genetics, drug discovery and neuroscience. Large-scale optical assays now routinely use thousands of high-resolution images to offer critical insights into the human body, our brain and the diseases that affect us. Today's optical microscopes and their associated image processing software, however, are still far from ideal. Current microscopes cannot form images with cellular-scale resolution over an area larger than a few square centimeters, which fundamentally limits our ability to monitor the detailed movements of living systems. For screening many in vivo model organisms, such as zebrafish, this limitation prevents current setups from simultaneously observing multiple freely moving organisms at cellular resolution, which makes high-resolution in vivo screening experiments challenging and time-consuming. It has also led to a scarcity of effective image processing software for high- resolution organism image analysis. Proposal: Over the course of successful Phase I and Phase II projects, Ramona Optics has developed a new “micro-camera array microscope” (MCAM) that overcomes the above limitations by capturing video with up to 1 gigapixel per frame, which can resolve hundreds of freely-swimming organisms at near-cellular-level detail (5 µm/pixel). In this proposal, Ramona Optics will produce a suite of software that takes full advantage of the MCAM's information-rich recordings. This software will automatically track and measure key morphological and fluorescence features across all zebrafish within a full well plate, simultaneously, to replace currently tedious and time-consuming tasks. Our MCAM and its new software will transform current toxicology and pharmacology research that relies on in vivo organism screening, by producing more experimental insights in less time and with higher accuracy and repeatability than current methods. SA1: MCAM software for parallelized larval tracking and video registration: Ramona Optics will produce Python software to track, crop and register all larvae within the MCAM FOV to produce per-larvae centered video for subsequent morphological analysis. We will demonstrate the ability to register video of hundreds of larvae imaged simultaneously (<0.1% error rate) to reduce saved data by 40X and produce standardized per-organism datasets. SA2: Automated annotation of morphological endpoints: Working with the Tanguay Lab at Oregon State University and the Yoder Lab at NC State University, we will create algorithms to automatically compute 10 larval zebrafish morphological endpoints, such as gaze direction, pectoral fin position, and body curvature, which we will verify in a series of toxicology titration experiments (validated across labs) to demonstrate at least 100X speed-up to current screening methods. SA3: Automated bright-field video analysis: We will then extend our automated morphology analysis software to brig...