Tallahassee, FL, United States of America

Adrian Barbu

This inventor holds 25 USPTO granted patents and 1 published patent application, plus 1 CIPO patent, primarily in Image Processing. Top assignees: Siemens Medical Solutions USA, Inc., Siemens Aktiengesellschaft, The Florida State University Research Foundation, Inc.. Active years: 2009-2018.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Adrian Barbu. Retrieved from https://idiyas.com/inventor/adrian-barbu

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

USPTO Granted Patents = 25 

% Patents Active = 48.0


Average Co-Inventor Count = 4.0

ph-index = 9

Forward Citations = 338(Granted Patents)


Location History:

  • Plainsboro, NJ (US) (2009 - 2011)
  • Tallahassee, FL (US) (2010 - 2018)

Company Filing History:


Years Active: 2009-2018

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Areas of Expertise:
Image Processing
Segmentation
Noise Reduction
3D Modeling
Fluoroscopy
Computed Tomography
Polyp Detection
Heart Modeling
Discriminative Models
Guidewire Tracking
Data Evaluation
Hierarchical Parsing
25 patents (USPTO):Explore Patents

Introduction

Adrian Barbu, based in Tallahassee, FL, is a notable inventor known for his groundbreaking work in the field of medical imaging technologies. With a total of 25 patents to his name, he has significantly contributed to the advancement of image processing and data analysis, particularly through the application of convolutional neural networks (CNN).

Latest Patents

Two of his latest patents showcase his innovative approach to image processing and computed tomography (CT) data analysis. The first patent is titled "System and method for image processing using automatically estimated tuning parameters." This invention describes a highly sophisticated image processing system that utilizes a trained convolutional neural network to optimize tuning parameters for images of interest. The system generates performance curves from a dataset of training images and employs a loss function to fine-tune the CNN for effective image processing.

The second patent, "Method and system for hierarchical parsing and semantic navigation of full body computed tomography data," presents an advanced approach to segment and navigate CT scans. This technology allows for the detection of organs and anatomic landmarks within CT volumes, enhancing the accuracy of medical diagnoses. The method utilizes a discriminative anatomical network to segment various organs such as the heart, liver, and kidneys, providing invaluable data for medical professionals.

Career Highlights

Adrian Barbu has built a distinguished career in the medical technology sector. He has worked with prominent organizations such as Siemens Medical Solutions USA, Inc. and Siemens Aktiengesellschaft, where he has honed his skills in imaging technology and deep learning applications. His experience in these innovative companies has equipped him with the necessary expertise to develop breakthrough technologies that positively impact healthcare.

Collaborations

Throughout his career, Adrian has collaborated with respected colleagues, including Dorin Comaniciu and Bogdan Georgescu. These collaborations have enabled the development of advanced methodologies, further pushing the boundaries of what is achievable in medical imaging.

Conclusion

Adrian Barbu's contributions to the field of medical imaging are noteworthy, marked by his 25 patents that reflect his innovative spirit and dedication to advancing technology. His work not only enhances the field of image processing but also plays a crucial role in improving patient diagnostics and outcomes in healthcare. As he continues to develop and refine his inventions, Adrian Barbu remains a key figure in the ongoing evolution of medical imaging technologies.

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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