Reveal is developing a pipeline of AI-based digital assays on the imageDx pathology platform for preclinical research, clinical trials, and decision support.
Advancing Research, Improving Patient Outcomes
Automated image quality control including focus assessment (detection and exclusion of out of-focus fields of view), tissue artifact detection and exclusion (folds, tears, slide debris, etc.), and staining artifact detection & exclusion.
AI-based cell segmentation offers increased accuracy over more traditional image analysis techniques. Access automated cell-by-cell quantitative immunohistochemistry (IHC) analysis paired with over 250 optimized IHC protocols.
AI-based cell segmentation and spot detection offer increased accuracy over more traditional approaches. Access automated cell-by-cell quantitative in situ hybridization (ISH) analysis including multiplex ISH in bright field or fluorescence.
A portfolio of advanced AI models to detect specific cell types in H&E stained sections. Examples include tumor profiling (automated segmentation and quantification of tumor, stroma, inflammatory & necrotic regions) as well as a growing library of tissue structures and disease endpoints.
Reveal has a world class team of data and research scientists building AI tools to address some of the biggest problems in healthcare through the most objective scalable pathology possible. We’re always interested in new data sets, research problems and clinical opportunities. Contact us to learn more.
Experience the power of multi-omic data. Pathology, genomics, and AI approaches are combined to generate large data sets, integrated data analysis and novel visualization.
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