Search with clinical terminology
Openda supports searches using SNOMED terms, synonyms, and related terms to help users identify relevant imaging and patient data.
De-identified imaging data and research tools for healthcare AI and clinical research teams.
Segmed provides access to de-identified medical imaging data and supporting tools for healthcare research and product development. Its Openda platform lets clinicians, researchers, and AI developers search imaging datasets and health records, while Segmed also offers custom dataset curation and tools for managing provider-held data. The service supports work across life sciences, medical devices, healthcare technology, and academic research.
Openda supports searches using SNOMED terms, synonyms, and related terms to help users identify relevant imaging and patient data.
Users can group studies by patient and sort by date, modality, or body part to review a patient's imaging over time.
Imaging datasets can include radiology reports and metadata, with connections to EHR records, pathology slides, and other non-radiology sources.
The network includes CT, MRI, X-ray, ultrasound, PET/CT, PET/MR, DEXA, mammography, echocardiography, and fluorescence imaging.
Incognito identifies and redacts protected health information in DICOM images and medical text reports, including information in text, metadata, and pixel data.
Piper supports scalable extraction and transfer from data silos; Openda can be used to search, filter, and build cohorts from an organization's own data.
AI teams can find real-world imaging data for model training and test performance across varied studies and clinical settings.
Life sciences researchers can use longitudinal imaging, reports, and available health records to investigate disease progression, treatment history, or outcomes.
Medical device teams can source training or validation datasets for algorithm development and FDA or CE-related evidence needs.
Research groups and healthcare organizations can de-identify DICOM images and reports before using them in research workflows.
Healthcare data teams can extract records from internal silos and use search, filters, and cohort-building tools to explore their own imaging data.
Segmed describes a network spanning CT, MRI, X-ray, ultrasound, PET/CT, PET/MR, DEXA, mammography, echocardiography, and fluorescence, with associated reports, metadata, and connections to other health data.
Openda is Segmed's data platform for searching, sorting, and exploring medical imaging datasets and health records. It includes tools for grouping studies by patient and building cohorts.
Yes. Segmed describes Incognito for de-identifying medical reports and DICOMs, Piper for extracting and transferring data from silos, and Openda for exploring an organization's data.
Segmed's Incognito tool identifies and redacts protected health information from DICOMs and medical text reports, including text, metadata, and pixel data. Segmed states that Incognito follows HIPAA Safe Harbor standards.
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