This inventor holds 3 USPTO granted patents and 1 published patent application and 1 EPO patent. Top assignees: Albert-Ludwigs-Universitat Freiburg, New York University, Universitaetsklinikum Freiburg. Active years: 2015-2019.
Company Filing History:
2 out of 94 
2 out of 1,726 
1 out of 40 Years Active: 2015-2019
Title: Valerij Kiselev: Innovator in Brain Imaging Technologies
Introduction
Valerij Kiselev is a prominent inventor based in Freiburg, Germany. He has made significant contributions to the field of brain imaging technologies, holding a total of 3 patents. His work focuses on advanced methods for analyzing brain microstructures and fiber tracking.
Latest Patents
Kiselev's latest patents include innovative systems and methods for obtaining and determining mesoscopic structures and orientations through fiber tracking. One notable patent describes a system that generates resultant data regarding fiber tracts and anatomical structures. This system receives imaging data and predictive models to create comprehensive analyses of brain structures. Another patent focuses on determining brain microstructure parameters from diffusion magnetic resonance imaging signals. This method utilizes rotational invariants to generate tissue parameters, enhancing the understanding of brain tissue characteristics.
Career Highlights
Throughout his career, Valerij Kiselev has worked with esteemed institutions such as New York University and Albert-Ludwigs-Universität Freiburg. His research has significantly advanced the field of medical imaging, particularly in understanding the complexities of brain anatomy.
Collaborations
Kiselev has collaborated with notable professionals in his field, including Marco Reisert and Dmitry Novikov. These partnerships have contributed to the development of innovative imaging techniques and methodologies.
Conclusion
Valerij Kiselev's contributions to brain imaging technologies through his patents and collaborations highlight his role as a leading inventor in this critical area of research. His work continues to influence advancements in understanding brain structures and functions.