Corpus Analytica

Streamline radiology dataset preparation with advanced preprocessing techniques.

Manage incidental findings and schedule follow-up imaging efficiently.

Generate patient-friendly radiology result communications in plain language.

Close care gaps in radiology by ensuring recommended imaging is completed.

Expert guidance for configuring and optimizing AI-assisted radiology reporting tools.

Auto-detect imaging modality (CT, MRI, X-ray, US, etc.) from user input, DICOM file headers, or file analysis. Also use when the user mentions "what modality", "detect from file", "identify imaging type", or needs to classify imaging studies. For PACS queries, see pacs-workflow.

Design and execute validation studies for radiology AI models to ensure clinical reliability and compliance.

Integrate AI detection systems into PACS workflows for enhanced medical imaging analysis.

Query and retrieve DICOM objects via DICOMweb REST API for imaging data.

Integrate LLM APIs for advanced radiology tasks and workflows.

Ensure the quality of AI outputs by validating results and detecting errors.

Create and optimize structured radiology reports using standardized templates.

Analyze and extract key findings from structured and free-text radiology reports.

Access and apply professional radiology society guidelines for clinical decision-making.

Streamline your radiology dataset selection and access for AI development.

Links current findings to prior studies and related literature for comprehensive analysis.

Query PACS, retrieve studies, and manage radiologist worklists efficiently.

Create, optimize, and manage imaging referrals between providers to enhance referral quality.

Access and synthesize medical imaging research literature efficiently.

Manage and configure clinical radiology environments, including PACS and EHR settings.

A collection of AI agent skills tailored for medical imaging and healthcare workflows.

Enhance radiology report quality through systematic audits and feedback.

Evaluates medical image quality against clinical standards and identifies areas for improvement.

Automatically detects imaging modalities from user input or DICOM files.

Create clear and accessible patient education materials for imaging procedures and findings.

Retrieves and analyzes operational metrics from radiology information systems for enhanced decision-making.

Conducts detailed reviews of imaging studies for clinical and QA purposes.