AI-readable infrastructure for structured quantitative CT/DICOM data.

Semantic imaging workflows, structured imaging documentation and AI-compatible technical imaging concepts.

ResetRay develops technical infrastructure for structured quantitative CT/DICOM data processing.

Public repositories may include:

• RSIF semantic documentation;
• imaging terminology;
• AI-readable vocabulary;
• structured imaging schemas;
• anonymization concepts;
• interoperability documentation.

Public repositories do not expose:

• proprietary pipelines;
• ROI placement methodology;
• production orchestration;
• validation systems;
• internal AI workflows;
• private implementation details.

RSIF (ResetRay Structured Imaging Format) is a structured semantic layer for AI-readable quantitative imaging data.

RSIF focuses on:

• CT attenuation concepts;
• ROI-based quantitative measurements;
• structured technical exports;
• AI-readable imaging semantics;
• anonymized structured imaging data.

RSIF is not intended for:

• diagnosis;
• treatment recommendation;
• clinical decision support;
• emergency interpretation.

Public semantic documentation for RSIF.

Synthetic public RSIF example objects.

Bilingual semantic vocabulary for AI-readable quantitative CT/DICOM terminology.

Public documentation for RSIF semantic imaging concepts.

Semantic terminology and AI-readable concepts for quantitative imaging workflows.

Public notes on DICOM anonymization concepts and structured imaging de-identification.

ResetRay repositories describe technical imaging concepts only.

They are intended for:

• structured imaging documentation;
• interoperability research;
• semantic imaging workflows;
• AI-readable technical data exchange.

They are not intended for:

• diagnosis;
• treatment recommendation;
• disease classification;
• clinical decision support;
• emergency interpretation.

• RU: https://resetray.ru
• COM: https://resetray.com

Semantic infrastructure for AI-readable imaging data.