US 11,710,236 B1
Variable exposure portable perfusion monitor
Guillermo Aguilar, College Station, TX (US); and Aditya Pandya, Riverside, CA (US)
Assigned to THE REGENTS OF THE UNIVERSITY OF CALIFORNIA, Oakland, CA (US)
Filed by The Regents of the University of California, Oakland, CA (US)
Filed on Feb. 16, 2023, as Appl. No. 18/170,455.
Claims priority of provisional application 63/362,912, filed on Apr. 13, 2022.
Int. Cl. G06T 7/00 (2017.01); G06V 10/62 (2022.01); G06V 10/88 (2022.01)
CPC G06T 7/0016 (2013.01) [G06V 10/62 (2022.01); G06V 10/895 (2022.01); G06T 2207/30104 (2013.01); G06V 2201/07 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method of imaging a target, comprising:
acquiring, by a processor of an imaging apparatus, multiple images of the target, wherein the multiple images have different exposure values;
determining temporal variances for the multiple images, wherein the temporal variances are determined over pixel regions having predetermined dimensions over a pre-defined number of images over a period of time, and wherein the temporal variance of a given pixel region represents a difference between a square of mean square values of the pixels in the given pixel region over a pre-defined number of frames, N, where N is a positive integer, and a mean value of square values of the pixels over the pre-defined number of frames;
determining spatial variances for the multiple images, wherein the spatial variances are determined over the pixel regions having predetermined dimensions, and wherein a spatial variance of a given pixel region represents a difference between a mean value of squares of pixel values and a square of a mean value of pixels in the region; and
generating a perfusion image of the target by combining the temporal variances and the spatial variances such that a local flow rate in the perfusion image at a given pixel is a function of changes in the spatial variances and the temporal variances as a function of exposure values;
wherein the generating the perfusion image comprises evaluating an average according to:

OG Complex Work Unit Math
wherein N is a total number of exposures collected, IPERF represents pixel value at each pixel location of the perfusion image, IEiSPAT/TEMP and IEi+iSPAT/TEMP represent spatial or temporal variances at corresponding pixel location for exposure times Ei and Ei+i, WEi and WEi+i are real numbers representing a relative weight for each exposure.