Radiology Report Generation Using AI Segmentation and Speech-to-Text

ChangeBridge: Patent Apps - Health Informatics (G16H)

Published April 2nd, 2026

Detected April 2nd, 2026

Summary

USPTO published patent application US20260094682A1 for a system and method of automatically generating radiology reports using AI. The invention processes medical images through segmentation and classification models, incorporates radiologist speech input converted via NLP, and generates structured reports with annotations. The patent names inventors Nivedha Srinivasan and Mouleeswaran Kumar, with application number 18901905.

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What changed

This patent application covers a system for automatic radiology report generation comprising: a segmentation model to identify structures in medical images; a classification model to categorize those structures; a speech-to-text component capturing radiologist dictation; an NLP model to convert speech to text; and an AI model to generate formatted radiology reports with image annotations. The system integrates with a radiologist user device for real-time display and input.

Patent applications do not impose regulatory obligations on third parties. Healthcare providers, medical imaging software developers, and medical device manufacturers may review this publication to understand competitive landscape in AI-driven radiology tools. No compliance actions, deadlines, or penalties are associated with this document. Technology companies developing medical imaging AI may consider this prior art when designing similar systems.

Source document (simplified)

← USPTO Patent Applications

SYSTEM AND METHOD FOR AUTOMATIC GENERATION OF A RADIOLOGY REPORT

Application US20260094682A1 Kind: A1 Apr 02, 2026

Inventors

Nivedha SRINIVASAN, Mouleeswaran KUMAR

Abstract

Various systems and methods are provided for automatically generating a radiology report. A medical image of a region of interest of a subject may be received. A structure of the region of interest of the subject may be segmented using a segmentation model and classified using a classification model. The medical imaging including the classified structure may be displayed via a user device of a radiologist. Speech data of the radiologist related to the classified structure may be received from the user device. Text data corresponding to the speech data may be generated using a natural language processing model. A radiology report corresponding to the medical image may be generated in a predetermined format using an artificial intelligence model. The radiology report including the medical image and an annotation including the generated text data in relation to the classified structure may be displayed via the user device of the radiologist.