Siemens Aktiengesellschaft

Siemens Corporation

Steven Michael Shea

Klaus J Kirchberg

Christine Lorenz

Sunil Goraksha Patil

Julien Christian Barbot

Erik John Tryggestad

Teboh Roland

A method of dynamic imaging and resolving respiratory motion includes acquiring volume data for a volume over a plurality of respiratory cycles, acquiring respiratory data representative of respiration over the plurality of respiratory cycles, dividing each respiratory cycle of the plurality of respiratory cycles into a set of respiratory intervals based on the respiratory data, and displaying a respective composite three-dimensional image of the volume for each respiratory interval based on the volume data acquired during the respiratory interval from each respiratory cycle of the plurality of respiratory cycles.

Respiratory interval-based correlation and processing of dynamic imaging data

Small tissue property change detection is provided for magnetic resonance (MR) guided intervention. T1 changes from before and after treatment are compared. The comparison identifies locations of possible change. The comparison is performed for different times, one before and one after a zero-crossing of a signal intensity time curve. Due to the characteristics of the T1 mapping, common locations from the different times will have reversed contrast. Clustering and this reversal are used to distinguish the treatment region from noise.

Small tissue property change detection in magnetic resonance guided intervention

Localization of a coil is provided for magnetic resonance (MR)-guided intervention. A multi-scale decomposition and characteristic transitions in the power spectra for the coil are used to determine a distribution of likelihood of the coil being at each of various locations and/or to determine a confidence in the position determination. For example, the power spectra along each axis is used to generate a likelihood distribution of the location of the coil. The power spectra are decomposited at different scales. For each scale, the modulus maxima reflecting transitions in the power spectra are matched using various criteria. A likelihood is calculated for each of the matched candidates from characterizations of the matched candidates. The likelihood distribution is determined from a combination of the likelihoods from the various scales.

Localization of a device for MR-guided intervention

Growing community of inventors

Baltimore, MD, United States of America

Steven Michael Shea