Bengaluru, India

S Raghu Menon

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Psip2 LLC. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: S Raghu Menon. Retrieved from https://idiyas.com/inventor/s-raghu-menon

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 1 

% Patents Active = 100.0

Average Co-Inventor Count = 6.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: S Raghu Menon and Medical Image Annotation

Introduction

S Raghu Menon is an inventor based in Bengaluru, India. His patent work focuses on creating annotated medical-image datasets for machine-learning applications.

Latest Patents

Menon is associated with 1 patent, titled “Generating Ground Truth Annotated Dataset for Analysing Medical Images.” The invention describes a semi-automated method for preparing annotated datasets to support lesion segmentation in medical images. It uses a trained segmentation model to generate masks, applies a geometric filter to validate them, and updates the model using validated masks. The updated model then generates further masks, which an operator can review through a user interface. Images with validated masks are selected to form the ground-truth dataset.

Career Highlights

Menon works at Psip2 LLC. His patent reflects an approach to combining machine-learning segmentation, geometric validation, and operator review in the preparation of medical-image datasets.

Collaborations

Menon’s listed coworkers include Prithvi Prakash and Warsha Barde.

Conclusion

S Raghu Menon’s patent centers on a semi-automated workflow for producing validated, annotated medical-image datasets for lesion-segmentation research.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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