De-identified imaging datasets
Segmed positions its dataset as de-identified medical imaging data, with DICOM images, radiology reports, and metadata available for research-oriented workflows.
Segmed is a real-world medical imaging data platform for research, AI teams and life sciences, with de-identified images, reports and records.
Segmed is a real-world imaging data platform focused on de-identified medical images, reports, and related records for AI development, clinical research, and life sciences workflows. The company describes itself as a source of regulatory-grade medical imaging data and a platform for making those studies available at scale.
Its Openda product is positioned as the company’s proprietary data platform for exploring and accessing imaging datasets. The site emphasizes search, patient-level navigation, and secure access to diverse datasets sourced from healthcare partners, with intended use across research, validation, and data management tasks.
Segmed positions its dataset as de-identified medical imaging data, with DICOM images, radiology reports, and metadata available for research-oriented workflows.
The platform is described as supporting longitudinal studies and multimodal data, including imaging studies and related records for research and validation use cases.
Openda includes search assistance with synonym support through SNOMED term selection, helping users locate relevant cases more precisely.
Users can group studies by patient and sort them by date, modality, or body part to move through longitudinal imaging records more efficiently.
The source says Openda aggregates imaging data from hospitals, imaging centers, and teleradiology clinics into a single dataset for analysis.
Segmed describes privacy and security controls around access to sensitive health information, and its broader site links to compliance and security resources.
Teams building diagnostic or triage models can use de-identified imaging datasets to support training and iterative development.
Organizations preparing submissions or internal evidence packages can use imaging data and related records for validation workflows and performance testing.
Researchers studying disease progression or treatment timelines can review longitudinal studies at the patient level and sort by date or modality.
Life sciences, medical device, and academic teams can use diverse datasets to support clinical research, feasibility, and comparative analysis.
Data management teams can use the platform’s de-identification and exploration tools to prepare and organize imaging data for downstream use.
Segmed provides a platform for accessing de-identified medical imaging data and related records for AI, research, and clinical data workflows. The site also describes Openda as Segmed’s proprietary data platform for searching and working with imaging datasets.
The source describes use by life sciences, medical device, technology, healthcare provider, CRO, pharmaceutical, and academic teams that need imaging data for research, validation, or data management workflows.
The site presents Openda as a self-serve platform with search, patient sorting, and data access features. It is described as a place where users can register for an account and access some imaging data right away.
The pricing page at `/pricing` is currently not available on the site, so pricing and commercial terms are not verified in the source material.
The source highlights de-identification and security-related controls, and it also links to security, privacy, trust, and compliance pages. Specific certifications should be confirmed directly from those pages before relying on them.