Foundation of
Healthcare AI Blog
Covering RedBrick AI's company & product updates and the state-of-the art in Radiology AI.
RedBrick AI Spring 2025 Product Updates
Key updates including Analytics 2.0, platform upgrades like project archiving and taxonomy import/export, Boost auto-start and BYOM configuration, multi-org management, URL filters, improved comments, expanded SDK, and various fixes.
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RedBrick AI Q4 2024 Product Updates
Discover the latest RedBrick AI platform enhancements including Consensus 3.0 with Manual Merge capabilities, improved Boost functionality for AI-assisted segmentation, new Folder Mode for better task organization, Weekly Summary Emails, Bring Your Own Model support, and Annotation Overlays for reviewers.
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RedBrick AI September 2024 Product Updates
Explore RedBrick AI's Q3 2024 updates including the new SAM2-powered Mask Propagation Tool, Document Viewer for radiological reports, Read-only Labels, Study Selector for better DICOM organization, Label Groups, Customizable Hotkeys, and support for new formats like MHD, MHA, and DCE MRI.
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RedBrick AI August 2024 Product Updates
Introducing 3D F.A.S.T. mode, Worklists for task management, expanded analytics for projects and tasks, taxonomy duplication, improved settings access, 3D heatmaps, and cached environment settings.
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RedBrick AI July 2024 Product Updates
Introducing heatmap visualization, sections for project organization, AltaDB launch, enhanced video tools including segmentation for 2D DICOM video, Cineloop for 3D volumes, and improved AWS integration.
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Automated Segmentation of Healthy Abdominal Organs Using CT Segmentator
Learn how to leverage CT Segmentator for automated segmentation of 117 anatomical structures in CT scans. This guide covers the setup process, taxonomy creation, project configuration, and automated segmentation workflow using the CHAOS dataset for healthy abdominal organs.
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Liver Tumor segmentation: F.A.S.T. vs Edge Selection with Contour tool
Learn how the FAST tool compares to the contour tool for segmenting a liver tumor.
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Case Study: Annalise.ai's Comprehensive Radiology AI Solutions with RedBrick AI
An in-depth look at how Annalise.ai leverages RedBrick AI to power their comprehensive radiology AI solutions. Learn about their approach to deep and broad AI algorithms, annotation management at scale, and how RedBrick AI's platform enables reliable and efficient medical image labeling.
Read More →RedBrick 1.0: Major Platform Updates Coming April 6th, 2024
Introducing RedBrick 1.0 with workspaces, self-hosted Boost add-on, enhanced contouring tools, improved project workflows with task clawback and archiving, and upgraded commenting system.
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Data Curation and Cohort Creation on RedBrick AI
A comprehensive guide on using RedBrick AI's cohort creation features for data curation and study preparation. Learn how to upload, index, filter, and organize medical imaging data with metadata management, manual classification, and distribution analysis tools.
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Redefining neurovascular and vascular care - RapidAI & RedBrick AI
RapidAI is a global leader in using artificial intelligence (AI) to combat life-threatening vascular and neurovascular conditions. Their products are used in more than 2,200 hospitals in over 100 countries to help physicians make faster, more accurate decisions for better patient outcomes.
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Lesion Detection in Mammography, DBT, and Breast MRI
A comprehensive guide on using RedBrick AI for multi-modality breast imaging analysis. Learn specialized workflows for mammogram hanging protocols, DBT lesion detection using cineloop, and 3D tumor detection in breast MRI with synchronized viewing capabilities.
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FDA Clinical Validation Study for Chest X-ray Anomaly Detection
A comprehensive walkthrough on setting up and conducting FDA clinical validation studies for chest X-ray anomaly detection algorithms using RedBrick AI. Learn how to implement complex workflows including inter-annotator agreement measurement, blinded vs unblinded CAD annotation comparisons, and validation checks.
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Guide: Segmentation of Large Organs in Abdominal CT Scans
A comprehensive guide on segmenting large organs like kidneys, liver, and pancreas using RedBrick AI's advanced tools. Learn multiple segmentation techniques including 3D Brush with masking, 3D Contour Tool, and F.A.S.T. AI-assisted segmentation.
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Guide: Volumetric Segmentation of Necrosis and Edema
A detailed walkthrough on segmenting high-grade gliomas using RedBrick AI. Learn how to use multiple MRI sequences (T1W, T1CE, T2W, FLAIR) to accurately segment necrosis and edema, with advanced techniques for contour tools and overlapping segmentations.
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Guide: Segmenting the Aorta and Iliac Arteries in Abdominal CTA Scans
A comprehensive guide on using RedBrick AI's tools and workflows to segment the aorta and iliac arteries in abdominal CTA scans. Learn how to set up your project, use region growing for base segmentation, and apply boolean operations for detailed arterial classification.
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Select Balanced Dataset with Cohort Creation, and New Annotation Tools!
Introducing Cohort Creation beta for intelligent dataset filtering, new lazy loading for improved DICOM performance, adaptive brush tool for precise segmentation, and new Project Manager role for enhanced workflow management.
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RSNA 2023, Annotation Version Explorer, Semantic Segmentation Export and More!
Visit us at RSNA 2023, explore new features including Annotation Version Explorer for version control, semantic segmentation export options, enhanced taxonomy UI with nesting and hints, and improved model evaluation capabilities.
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The Power of Digital Twins
Discover how digital twins are revolutionizing personalized medicine by creating virtual patient models. Learn how these AI-driven computational representations enable treatment simulation and optimization, with real-world applications in cardiac care and beyond.
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RedBrick AI at BioTech X, Webinar, and Annotation Reference Standards
Join us at BioTech X Switzerland, register for our first annotation tool webinar demo, and explore new features including reference standards for training and an improved UI with quick tutorials.
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The Potential of AI in Sickle Cell Disease
Explore how artificial intelligence is transforming the diagnosis, treatment, and management of sickle cell disease. From early detection to personalized treatment plans and remote monitoring, discover the innovative ways AI is offering new hope to millions affected by this genetic disorder.
Read More →Quick Image and Segmentation Visualization with Preview Mode!
Introducing Preview Mode for instant visualization of images and segmentations, enabling quick model prediction audits and seamless viewing of DICOM, NIfTI, NRRD formats directly in the browser.
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Privacy Policy & F.A.S.T. Updates, Version History for Annotations, and More Formats
Important updates including F.A.S.T. enterprise tier announcement, customizable tool settings, label version history, new format support for NRRD and RT-Struct, and enhanced time-based filtering capabilities.
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Cinematic 3D Visualization, Custom Meta-Data, and More!
Introducing cinematic 3D visualization with de-coupled windowing, 2D segmentation outline view, custom metadata upload capabilities, SAML and Google SSO support, task priorities for active learning, and improved layout management.
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Accessible Healthcare Using AI - Qure.ai & RedBrick AI
Discover how Qure.ai uses RedBrick AI to build AI solutions that make healthcare more accessible and affordable. Learn how their team leverages our platform to develop CE-certified products for automated interpretation of radiology exams, serving over 10 million patients annually across 70 countries.
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Improved Diagnosis for Life - Olea Medical & RedBrick AI
Learn how Olea Medical, a Canon Medical Systems company, uses RedBrick AI to develop intelligent MRI and CT imaging solutions. Discover how their team leverages our platform to create innovative diagnostic tools used by over 250 research institutions worldwide.
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Insight Based Decision Making - Radiomics & RedBrick AI
Discover how Radiomics, a Belgium-based MedTech scale-up, uses RedBrick AI to optimize clinical trials in oncology through AI-powered medical image analysis. Learn how their team leverages our platform for precise segmentation and feature extraction in radiomics analysis.
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Taxonomy Upgrades, 3D F.A.S.T., and Configurable Annotations Tools!
Major updates including nested taxonomies with hints, 3D F.A.S.T. capabilities for cross-slice segmentation, programmatic annotation tool configuration, and new view management features with full-screen mode.
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Introducing F.A.S.T: RedBrick AI's Fast Automated Segmentation Tool
We're excited to release our Fast Automated Segmentation Tool, powered by Meta AI's SAM, for medical imaging. Segment your DICOM & NIfTI data 10x faster with state-of-the-art AI segmentation integrated into RedBrick AI's web-based annotation platform.
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Large Study Support, Custom Tabs, & SOC-II Certification
Announcing SOC-II Type 1 compliance, major improvements to data loading with asynchronous series loading, enhanced memory management for large studies, and new custom layout tabs for flexible viewport configurations.
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Improved Access Control, Refreshed Personal Dashboard & Comment Pinning on Viewports!
Introducing new Project Admin role for improved access control, viewport comment pinning for better feedback, refreshed personal dashboard with key statistics, and beta release of ellipse and rectangle ROI tools.
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Intelligent Contouring with Interpolation and Workflow Flexibility!
Introducing new contouring tools with intelligent interpolation, improved workflow flexibility with draft submissions, and the ability to modify review stages, along with our exciting $4.6 million seed round announcement.
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5x faster manual segmentation
Building datasets for AI requires large amounts of time hand annotating data. The faster and more painless that process is, the better. We were able to make a purely manual annotation tool that speeds up segmentation by 500%.
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Powerful Labeling Taxonomies, Hanging Protocols, and Intellisync
Major updates including Taxonomy V2 with study & series level classifications, customizable hanging protocols for standardized layouts, Intellisync for multi-series synchronization, and new user tagging capabilities.
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Segmentation Mirroring, Custom Label Validation Scripts, and More!
Introducing advanced features including segmentation mirroring across MRI series, custom JavaScript validation for annotations, randomized review capabilities, maximum/minimum intensity projection, and a preview of our revamped taxonomy system.
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Qualify Annotations with Consensus, and a New Data Format!
Introducing our new consensus feature for quantifying annotation quality and generating higher quality ground truth, with multiple annotator support, automatic task assignment, inter-annotator agreement scoring, and review arbitration capabilities.
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Measurement Tools, Seamless Data Import & Multi-modality Support!
Introducing new measurement tools for 3D scans, improved data import with study/series structure support, multi-modality capabilities, and cross-reference lines for MRI scans, along with various UI improvements.
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Fast Data Loading, Upgrades to 2D Annotation and More!
Major performance improvements including DICOM task caching for faster loading, unified Medical data type with revamped 2D video & image annotation tools, and new bulk processing capabilities for tasks.
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DICOM Tool Redesign 🚀
Introducing our completely revamped DICOM labeling interface with a modern design, new context panel, overlapping segmentations support, improved annotation type selection, task queue filtering, and new Select attribute type.
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Introduction to DICOM Coordinate Systems
A comprehensive guide for ML/CV engineers to understand DICOM coordinate systems, image positioning, and orientation. Learn how to properly handle 3D medical images, measure in physical dimensions, and correctly order 2D slices.
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January 2022 Product Updates
Introducing a revamped Taxonomy Design with improved attribute management, new Benchmarking & Evaluation Tests for labeler quality control, and DICOM Tool updates including instance locking and 3D rendering performance optimizations.
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Introduction to DICOM for Computer Vision Engineers
DICOM (Digital Imaging and Communications in Medicine) is a standard for storing, processing, and transmitting medical images and related information. This blog is a light introduction into DICOM for data scientists and computer vision engineers.
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December 2021 Product Updates
Introducing the RedBrick CLI for data exports, new Label Auto-Saving feature, Individual Labeler Quality tracking, and major Segmentation Tool updates including a revamped 2-column structure and new pen & scissor tools.
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Designed and built for radiology AI.
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