Erick Martins Ratamero
I manage the Imaging Applications team at The Jackson Laboratory, working in the Research IT department and providing support on imaging data analysis and management to 60+ research groups. My main area expertise is in microscopy data analysis and management, with my previous life being the data person at the CAMDU core facility at Warwick Medical School. I have a PhD in Analytical Science, developing computational models of bacterial cell division, from the University of Warwick.
Sessions
Between telescopes and satellite cameras and MRI machines and microscopes, scientists are producing more images than they can realistically look at. They need specialized viewers for multi-dimensional images, and automated tools to help process those images into knowledge. In this tutorial, we will cover the fundamentals of algorithmic image analysis, starting with how to think of images as NumPy arrays, moving on to basic image filtering, and finishing with a complete workflow: segmenting a 3D image into regions and making measurements on those regions. At every step, we will visualize and understand our work using matplotlib and napari.
Image analysis is ubiquitous across many areas of biomedical research, resulting in terabytes of image data that must be hosted by both research institutions and data repositories for sharing and reproducibility. Common solutions for data hosting are required to improve interoperability and accessibility of bioimage data, while maintaining the flexibility to address each institution's unique requirements regarding sharing and infrastructure. OMERO is an open-source solution for image data management which can be customized and hosted by individual institutions. OMERO runs a server-based application with web browser and command line options for accessing and viewing image data, based on the widely used OME data model for microscopy data. Multiple OMERO deployments might be used to provide core delivery, facilitate internal research, or serve as a public data repository. The omero-cli-transfer package facilitates data transfer between these OMERO instances and provides new methods for importing datasets. Another open-source package, ezomero, improves the usability of OMERO in a research environment by providing easier access to OMERO's Python interface. Along with existing OMERO plugins built for other analysis and viewing software, this positions OMERO to be a hub for image storage, analysis, and sharing.