Lohr, Germany

Laura Pfaff

This inventor holds 2 USPTO granted patents. Top assignee: Siemens Healthineers Ag. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Laura Pfaff. Retrieved from https://idiyas.com/inventor/laura-pfaff-fugvo5xq

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

Calculating rank

Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2026

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2 patents (USPTO):Explore Patents

Title: Laura Pfaff and Image De-Noising Innovation.

Introduction

Laura Pfaff is an inventor based in Lohr, Germany. Her patent work includes a machine-learning training method designed to improve image de-noising.

Latest Patents

Pfaff is associated with 1 patent, titled “Training Method for a System for De-Noising Images.” The invention describes training a machine-learning model using complex-valued image repetitions. It first corrects the phases of the repetitions so their phases are consistent, then calculates signal images and a noise map based on the standard deviation between those images. The model is trained using the signal images, the noise map, and a loss function based on Stein’s unbiased risk estimator.

Career Highlights

Pfaff is associated with Siemens Healthineers AG. Her patent reflects the application of machine learning and statistical estimation to image processing.

Collaborations

The provided information identifies Tobias Würfl and Marcel Dominik Nickel as Pfaff’s coworkers. Their names are associated with her professional context, though specific roles in the patent are not stated.

Conclusion

Laura Pfaff’s patent describes a structured approach to training machine-learning systems for image de-noising, combining phase correction, noise estimation, and Stein’s unbiased risk estimator.

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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