ResetRay Platform Powered by SigmaBaksel Engine From Images to Structured Signal

ResetRay Platform is powered by SigmaBaksel Engine.

SigmaBaksel Engine evolved from earlier internal processing prototypes collectively referred to as AngioBaksel.

While AngioBaksel explored the concept of transforming imaging data into structured signal, SigmaBaksel Engine represents the current generation of the processing architecture used by ResetRay Platform today.

Canonical architecture:

CT/DICOM ↓ SigmaBaksel Engine ↓ Structured Signal ↓ RSIF ↓ Health Apps / AI / Software

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.