The primary goal is to create a large scale distributed image processing
infrastructure, the LIMPID, though a broad, interdisciplinary
collaboration of researchers in databases, image analysis, and sciences.
In order to create a resource of broad appeal, the focus will be on
three types of image processing: simple detection and labelling of
objects based on detection of significant features and leveraging recent
advances in deep learning, semi-custom pipelines and workflows based
on popular image processing tools, and finally fully customizable
analysis routines. Popular image processing pipeline tools will be
leveraged to allow users to create or customize existing pipeline
workflows and easily test these on large-scale cloud infrastructure from
their desktop or mobile devices. In addition, a core cloud-based
platform will be created where custom image processing can be
created, shared, modified, and executed on large-scale datasets and
apply novel methods to minimize data movement. Usage test cases will be
created for three specific user communities: materials science, marine
science and neuroscience. An industry supported consortium will be
established at the beginning of the project towards achieving long-term
sustainability of the LIMPID infrastructure.