Effortless, robust, adaptable and no code. Our platform Hero lets you seamlessly construct image processing pipelines by integrating predefined operations, all within an intuitive visual programming interface where you drag and drop everything from your data to a machine learning algorithm.
Designing a workflow is trivially easy and extremely fast using drag-and-drop, with hundreds of nodes available at your fingertips. Data types such as images, binary masks or tables are color coded to give a better overview and reduce the risk for errors.
The workflow can be executed at any time in the design process. The result of each step in the pipeline is saved in the node itself, which makes building, debugging and evaluating even the most advanced pipelines simple and intuitive.
Plugin nodes can easily be created using python, with full debugging support in external IDEs.
Focus only on the task you want to solve and leave image import, pre-processing, post-processing and visualization to Hero. Plugins can be inserted anywhere in the pipeline and can easily be shared between collaborators.
The image visualizer in Hero provides state-of-the-art visualization of medical image data, with up to six simultaneous viewports. Each viewport can show either 2D image projections or a 3D surface rendering, and viewport coordinate systems can be synchronized between viewports.
The visualizer also provides tools for defining regions of interest that can be used in the pipeline or saved to a database and used at a later point in the analysis process.
Streamline the analysis of large datasets by applying a workflow to multiple inputs. The batch processing results can be automatically aggregated to quickly generate insights and identify patterns across the entire dataset. This significantly reduces the time and effort required for data analysis .
A broad range of different export options are available in Hero. We support all common image formats for import and export. You can also send and receive images through DICOM nodes, so integrating Hero in the clinical pipeline for research purposes is simple.
Numerical values such as statistical information can be written to .csv or .xlsx files or to reports in .pdf format. Images can also be exported to all common image formats for presentation and publication purposes, including animated .gif files; and even exported to STL files used for 3D printing.
SPAARC lets you extract a large number of quantitative features from your medical images - no-code. This can be done on multiple modalities and is useful in several medical fields to identify or classify texture features or changes therein.
SPAARC is deployed as an add-on to Hero in collaboration with Cardiff University and certified via IBSI (read more) to ensure standardized feature extraction for all 165 texture features and available convolutional filters. Standardized, reproducible, automated and no coding.
Read more about SPAARC radiomics here
Hero Imaging is easy to use but still powerful and flexible. We let the user build image processing pipelines by combining predefined operations — all through an intuitive visual programming concept.
Visual programming is the core of Hero Imaging.
Hundreds of nodes are available and can be combined.
Visual programming is the core of Hero Imaging.
Hundreds of nodes are available and can be combined.
Visual programming is the core of Hero Imaging.
Hundreds of nodes are available and can be combined.
Visual programming is the core of Hero Imaging.
Hundreds of nodes are available and can be combined.
Visual programming is the core of Hero Imaging.
Hundreds of nodes are available and can be combined.
Visual programming is the core of Hero Imaging.
Hundreds of nodes are available and can be combined.
