US 12,243,625 B2
Method and apparatus for identifying and quantifying abnormality
Roger Zebaze, Coburg (AU); and Yu Peng, Box Hill (AU)
Assigned to CURVEBEAM AI LIMITED, Melbourne (AU)
Filed by CURVEBEAM AI LIMITED, Melbourne (AU)
Filed on Oct. 3, 2022, as Appl. No. 17/959,180.
Application 17/959,180 is a continuation of application No. 16/081,701, granted, now 11,462,302, previously published as PCT/AU2017/050172, filed on Feb. 28, 2017.
Claims priority of application No. 2016900806 (AU), filed on Mar. 3, 2016.
Prior Publication US 2023/0112205 A1, Apr. 13, 2023
Int. Cl. G16B 45/00 (2019.01); G06T 7/00 (2017.01); G16B 20/00 (2019.01); G16B 40/00 (2019.01); G16H 10/40 (2018.01); G16H 30/20 (2018.01); G16H 50/20 (2018.01)
CPC G16B 45/00 (2019.02) [G06T 7/0012 (2013.01); G16B 20/00 (2019.02); G16H 10/40 (2018.01); G16H 30/20 (2018.01); G16H 50/20 (2018.01); G06T 2207/10072 (2013.01); G06T 2207/30008 (2013.01); G16B 40/00 (2019.02)] 19 Claims
OG exemplary drawing
 
1. A computer-implemented method of building an abnormality quantifier comprising:
generating an image or map by imagizing at least one first selected dataset comprising measurements of a normal population or sample and at least one second selected dataset comprising measurements of an abnormal population or sample;
identifying a normality zone within the image or map using the at least one first dataset;
identifying an abnormality zone within the image or map using the least one second dataset;
determining a definition of normality based on the normality zone; and
determining a definition of abnormality based on a comparison of (i) the definition of normality and (ii) the abnormality zone;
wherein the abnormality is disease, fracture-vulnerability of bone, or obesity;
the measurements of the normal population or sample comprise co-measurements, being measurements that relate to respective characteristics of the normal population or sample, and the measurements of the abnormal population or sample comprise co-measurements, being measurements that relate to the respective characteristics of the abnormal population or sample; and
the co-measurements comprise two-or more dimensional ordered pairs, of either co-dependent or non co-dependent parameters.