Erlangen, Germany

Tino Hausotte



 

Average Co-Inventor Count = 2.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2020-2025

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2 patents (USPTO):Explore Patents

Title: Tino Hausotte: Innovator in Surface Data Quality Assessment

Introduction

Tino Hausotte is a notable inventor based in Erlangen, Germany. He has made significant contributions to the field of data processing, particularly in the assessment of surface data quality extracted from volume datasets. His innovative approach has implications for various applications in technology and data analysis.

Latest Patents

Tino Hausotte holds a patent for a "Method and system for determining the local quality of surface data extracted from volume data." The aim of this invention is to determine the local quality of surface data by utilizing a surface determination method. The process involves determining an environment in the volume data set for each surface point of the surface data. By analyzing the curve of the grayscale values of voxels from this environment, at least one quality characteristic is derived, which characterizes the quality of the respective examined surface point. The quality characteristic is then output along with the coordinates of the examined surface point as the method result.

Career Highlights

Tino Hausotte is associated with Volume Graphics GmbH, where he applies his expertise in data processing and surface quality assessment. His work has contributed to advancements in the field, enhancing the accuracy and reliability of surface data analysis.

Collaborations

Tino collaborates with Matthias Flessner, working together to push the boundaries of innovation in their field. Their combined efforts aim to improve methodologies and technologies related to surface data quality.

Conclusion

Tino Hausotte's contributions to the field of surface data quality assessment highlight his innovative spirit and dedication to advancing technology. His patent and work at Volume Graphics GmbH demonstrate the importance of quality in data analysis, paving the way for future advancements in this area.

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