Corpus Analytica

Automatically detects imaging modalities from user input or DICOM files.

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

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

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

Streamline your radiology dataset selection and access for AI development.

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

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

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

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

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

Streamline radiology dataset preparation with advanced preprocessing techniques.

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

Integrate LLM APIs for advanced radiology tasks and workflows.

Create and optimize structured radiology reports using standardized templates.

Manage incidental findings and schedule follow-up imaging efficiently.

Access and synthesize medical imaging research literature efficiently.

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.

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

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

Generate patient-friendly radiology result communications in plain language.

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

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

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

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

Enhance radiology report quality through systematic audits and feedback.

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

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