The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 05, 2020

Filed:

Apr. 21, 2017
Applicants:

New York Society for the Ruptured and Crippled Maintaining the Hospital for Special Surgery, New York, NY (US);

Medical College of Wisconsin, Milwaukee, WI (US);

Inventors:

Kevin Matthew Koch, Wauwatosa, WI (US);

Matthew F. Koff, Livingston, NJ (US);

Hollis Potter, Greenwich, CT (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/055 (2006.01); G01R 33/565 (2006.01); G01R 33/24 (2006.01); G01R 33/56 (2006.01); A61B 5/00 (2006.01);
U.S. Cl.
CPC ...
A61B 5/055 (2013.01); A61B 5/4528 (2013.01); G01R 33/243 (2013.01); G01R 33/56 (2013.01); G01R 33/56536 (2013.01);
Abstract

A method includes: accessing MRI data acquired from a joint area, the MRI data including a series of spatially mapped spectral data points; generating MRI images of the joint area; receiving information encoding a region of interest that encompasses a suspected metal particle deposition area over at least one of the MRI images; constructing magnetic field maps using the MRI data, each representing off-resonance frequency shifts over the joint area; removing a background of off-resonance field inhomogeneity from the magnetic field map such that the region of interest is free from off-resonance field inhomogeneity; identifying clusters from the magnetic field maps with the background of off-resonance field inhomogeneity removed, the clusters defined over a first dimension of offset frequencies and a second dimension of cluster volumes; and computing a quantitative metric by combining information from the identified clusters according to both the first dimension and the second dimension.


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