Epsilon3 is the leading AI-powered procedure and resource management tool designed for teams building, testing, and operating advanced products and systems.
✔ Save Time & Money
Avoid costly delays, mistakes, and inefficiencies by automatically tracking procedures and resources.
✔ Prevent Failures
Ensure the right step is completed at the right time with conditional logic and built-in revision control.
✔ Optimize Collaboration
Real-time progress updates and role-based sign-offs keep your stakeholders on the same page.
✔ Continuously Improve
Advanced data analytics and automated reporting enable rapid iteration and data-driven decisions.
Epsilon3 is trusted by industry leaders like NASA, Blue Origin, Firefly Aerospace, Sierra Space, Redwire, Shift4, AeroVironment, Commonwealth Fusion Systems, and other commercial and government organizations.
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Significantly improve the speed and quality of Radiology reporting by reducing unnecessary dictation, particularly for ultrasound and DEXA. Imorgon transfers modality measurements into Powerscribe/Fluency/RadAI merge fields/tokens, eliminating manual entry errors.
Imorgon's specialized services offer the following advantages:
- All measurements are always transferred (usually DICOM SR)
- Electronic worksheets capture findings and insert them into Powerscribe/Fluency/RadAI (rather than dictating from a worksheet)
- Worksheets with priors, calculators, and clinical decision support (TI-RADS, O-RADS, etc)
- Integrate into Epic or other EHRs
- Vendor neutral
- Support to ensure everything continues working
Significant improvement in the overhead of reporting with a quick ROI.
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Slice:Drop
Slice:Drop is an engaging online platform that allows for the exploration of medical imaging data in a three-dimensional format, providing users with the ability to quickly analyze scientific and medical visuals. It supports a variety of scientific file formats right from the beginning, including volumetric data, models, and fibers. Users can simply drag and drop their medical imaging files onto the interface, which eliminates the requirement for file conversions and facilitates immediate rendering. By employing WebGL and HTML5 canvas technology, the platform visualizes data in both 2D and 3D, utilizing its unique open-source toolkit known as XTK. A key feature of Slice:Drop is that all data processing is performed on the client side, ensuring that no information is sent over the internet, which helps to maintain user privacy and security. In addition, Slice:Drop offers an array of features such as adjusting the opacity of 3D visuals, configuring window/level settings, implementing thresholding techniques, and managing label map opacity for volumetric datasets. It also includes options for controlling visibility and opacity settings for mesh data, plus applying show/hide features and fiber length thresholds for fiber visuals. This comprehensive set of tools makes Slice:Drop an essential resource for medical professionals who need efficient and secure access to complex imaging data, ultimately enhancing their ability to make informed decisions based on the analyzed visuals.
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Elements Spine SRS
Brainlab's Elements Spine Stereotactic Radiosurgery (SRS) is an advanced software platform designed to optimize the treatment of spinal metastases. The workflow is characterized by its automation in every stage, which includes detailed anatomical mapping, adjustments for spinal curvature, and precise target identification, ensuring exceptional accuracy and consistency at submillimeter precision. A unique algorithm effectively addresses differences in spinal curvature, enhancing the reliability of image fusion. The system utilizes a patented synthetic tissue model for automatic segmentation, allowing for the accurate identification and labeling of various spinal levels essential for dose calculations. Additionally, tools for defining Gross Tumor Volume (GTV) contours are provided, along with automated recommendations for Clinical Target Volume (CTV) and a cropped spinal canal object that complies with International Spine Consortium Guidelines. The incorporation of AI-driven contouring features facilitates the rapid and accurate delineation of more than 200 anatomical structures, including lymph nodes. This technological development not only simplifies the treatment workflow but also significantly improves patient outcomes in the management of spinal cancer, reflecting a major leap forward in oncological care. As a result, healthcare professionals can deliver more tailored and effective treatment strategies for patients grappling with this challenging condition.
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