US 12,270,883 B2
Sparse representation of measurements
Guanhua Wang, Ann Arbor, MI (US); Matteo Alessandro Francavilla, San Mateo, CA (US); Thomas Witzel, Redwood City, CA (US); and Jeffrey H. Kaditz, Wilson, WY (US)
Assigned to Q Bio, Inc., San Carlos, CA (US)
Filed by Q Bio, Inc., San Carlos, CA (US)
Filed on Feb. 22, 2023, as Appl. No. 18/172,619.
Application 18/172,619 is a continuation of application No. 17/510,258, filed on Oct. 25, 2021, granted, now 11,614,508.
Prior Publication US 2023/0204700 A1, Jun. 29, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G01R 33/56 (2006.01); A61B 5/055 (2006.01); G01R 33/561 (2006.01); G06T 7/00 (2017.01)
CPC G01R 33/5608 (2013.01) [A61B 5/055 (2013.01); G01R 33/5611 (2013.01); G06T 7/0012 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/20081 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of performing a sparsity technique, comprising:
by a computer system:
updating a dictionary of predetermined features based at least in part on non-invasive measurements performed on an individual and historical non-invasive measurements;
determining weights associated with features in an updated dictionary of predetermined features based at least in part on the non-invasive measurements;
computing or selecting a sampling pattern based at least in part on the non-invasive measurements and the historical non-invasive measurements;
obtaining an image of at least a portion of the individual by performing additional non-invasive measurements based at least in part on the computed or selected sampling pattern, wherein the image comprises a sub-sampled or a compressed image; and
reconstructing a second image based at least in part on the image, the updated dictionary of predetermined features and the determined weights.