Company Filing History:
Years Active: 2018
Title: Innovations of Bryan Howell in Volume-Conductor Models
Introduction
Bryan Howell is an accomplished inventor based in Cleveland, OH (US). He has made significant contributions to the field of volume-conductor modeling, particularly in understanding anisotropic tissues. His innovative approach has led to the development of a unique patent that addresses complex challenges in this area.
Latest Patents
Bryan Howell holds a patent titled "Load-preserving method for defining anisotropy in volume-conductor models." This patent focuses on systems and methods for modeling conduction in a volume. In one embodiment, diffusion eigenvalues of a plurality of diffusion tensors are received. The diffusion tensors are associated with an anatomical structure that has heterogeneous and anisotropic tissues. The diffusion eigenvalues of the diffusion tensors are calculated from imaging data. Subsequently, one or more conductance ratios of a conductivity tensor are set based, at least in part, on one or more diffusion ratios of a corresponding diffusion tensor. The conductance eigenvalues of a conductivity tensor can then be calculated based, at least in part, on the one or more conductance ratios of the conductivity tensor. A volume-conductor model of the anatomical structure is generated based, at least in part, on the plurality of calculated conductivity tensors. Bryan Howell has 1 patent to his name.
Career Highlights
Bryan Howell is affiliated with Case Western Reserve University, where he continues to advance research in his field. His work has been instrumental in enhancing the understanding of conduction in complex biological systems.
Collaborations
One of his notable collaborators is Cameron C McIntyre, with whom he has worked on various projects related to his patent and research interests.
Conclusion
Bryan Howell's innovative contributions to volume-conductor modeling demonstrate his expertise and commitment to advancing scientific knowledge. His patent reflects a significant step forward in understanding anisotropic tissues and their implications in medical imaging and analysis.
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