A nucleus of computational activity and collaboration at scale. Vision Hub enables design and execution of large-scale experiments that produce results from images, whether datasets are already stored or are actively being produced. Mass quantities of Imagery are onboarded and processed by a virtual team of computational workers that come to life when you need them and smartly utilize processing cores in servers or workstations. When lots of images need to be processed, we approach the maximum speeds possible. Your researchers can make analysis pipelines in the Vision4D GUI and upload these to the Hub where they can be vetted and used by others. Also, your computing experts can leverage and parallelize their own innovative processing algorithms via convenient API’s.
Create tailored and optimized workflows that extract valuable information from your stores of images. Run at scale to produce results faster and spanning all levels of analysis. Examine and share the results or expose them to AI.
Scientific images have varying spatial dimensions (2D or 3D), timings (still or time-lapse), numbers of channels, and regions of interest (continuous tiles or disconnected views). It’s essential that ALL kinds of images at ALL size scales, tiny to massive, are securely stored and easily accessed for imaging science workflows. arivis applications can monitor image production and onboard images as they are created. Flexible importers enable custom structuring of image files inside the Scalable Image Storage (SIS) format.
Inspection of images and results must occur at many times at many steps in imaging science workflows. Quality checks after acquisition and processing ensure that raw data are correct and ready for accurate analysis. At the end, direct interactive visualization of results on raw images provide an instant view of patterns in data. Viewers in arivis applications provide fast visual access to support immediate quality checks and discovery of results. Scalable Image Storage (SIS) files are always viewable, even during processing.
A host of algorithms improve and standardize background and noise characteristics of images or stitch together 3D regions of interest (for example, for whole organ imaging). Notably, new AI-based reconstruction algorithms can now make incredible image enhancements. arivis lets you quickly evaluate a multitude of processing and enhancement strategies to discover the optimal ones for your images. Processing is highly parallel and proceeds with speed and efficiency.
The process of producing spatially resolved objects on scientific images drives verified discoveries and conclusions. There are many different approaches to creating results objects whether they exist in a volume, over time, or represent a collection, or class, of associated objects. arivis applications enable you to leverage the right approach for your data and databases of objects for each image can contain useful computed features. Each image’s story is told in relevant objective measurements that can always be viewed on the raw or enhanced images.
High quality images and sets of results must be distilled to provide snapshots of project progress and outcomes. Rather than directly converting results to external formats, it’s often more efficient to first summarize them in the framework used to view the images and create the results. This saves time and enables efficient feedback loops. Flexible charting in arivis affords custom summaries of measurements while high-res rendering gives information-rich views of each image or time-series. Users can export results (tables, surfaces, renderings, etc.) as they like.
High-throughput and enterprise-level imaging science produce results across a huge number of images and experiments. Unfortunately, in many campuses and organizations these results are completely disconnected, which means powerful metanalyses are not possible or extremely costly. The arivis environment can be configured to expose spatially resolved results, summaries of results, and raw data contained by results objects to metanalysis algorithms - including AI.
Imaging systems - Revolutionary fluorescence, CT, EM, high-content, MRI, and histology systems digitize your experiments. Images are a heavy data burden but can contain incredible information. Traditionally, entire image files had to be transferred to view even just small parts of images. arivis applications take any images and convert them into Scalable Image Storage (SIS), enabling access to any part of any dataset, of any size, at any time, for visualization, computation, or examination of results.
Datasets - Scientific images are stored on computers, workstations, and servers throughout your organization. The machines often lack power for the heavy image processing required to produce results rapidly. We efficiently access files to enable experts to inspect data or design computational pipelines. Datasets from anywhere can be registered to the Hub to eliminate bottlenecks and data silos.
Experts - Your scientists have ideas about how to extract information from images. Currently, they may have to rely on special staff to help them connect datasets to computational servers and run jobs. The Hub makes it easier to submit jobs for computation and enables you to add computational capacity as you need it, whether onsite or in the cloud.
Processing Servers - Powerful computing is available on your campuses but may not be used to the fullest. When not used, servers take up space, consume energy, and depreciate, while information hides in image storages. Offsite resources can be leased for bursts of capacity.
The Hub collects processors into a computational resource and smartly divvies jobs to achieve maximum throughput and efficiency.