US 11,918,336 B2
Reduced feature generation for signal classification based on position weight matrix
Taous Meriem Laleg, Thuwal (SA); Fahad Ali Albalawi, Thuwal (SA); and Abderrazak Chahid, Thuwal (SA)
Assigned to KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY, Thuwal (SA)
Appl. No. 17/430,109
Filed by KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY, Thuwal (SA)
PCT Filed Feb. 14, 2020, PCT No. PCT/IB2020/051272
§ 371(c)(1), (2) Date Aug. 11, 2021,
PCT Pub. No. WO2020/170101, PCT Pub. Date Aug. 27, 2020.
Claims priority of provisional application 62/893,452, filed on Aug. 29, 2019.
Claims priority of provisional application 62/807,511, filed on Feb. 19, 2019.
Prior Publication US 2022/0147756 A1, May 12, 2022
Int. Cl. A61B 5/055 (2006.01); A61B 5/00 (2006.01); G06F 18/2431 (2023.01); G06T 7/00 (2017.01); G06T 11/00 (2006.01)
CPC A61B 5/055 (2013.01) [A61B 5/0042 (2013.01); G06F 18/2431 (2023.01); G06T 7/0012 (2013.01); G06T 11/008 (2013.01); A61B 5/7267 (2013.01); A61B 2576/026 (2013.01); G06F 2218/12 (2023.01); G06T 2207/10088 (2013.01); G06T 2207/30016 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for classifying input data of a 3-dimensional object, the method comprising:
receiving the input data that describe the object, wherein the input data corresponds to plural classes;
associating the input data with voxels that describe the object;
calculating a real-number sequence X(n), which is associated with a measured parameter P that describes the object;
quantizing the real-number sequence X(n) to generate a finite set sequence Q(n), where M describes a number of levels;
generating a voxel-based weight matrix for each class of the input data; and
calculating a score S for each class of the plural classes, based on a corresponding voxel-based weight matrix,
wherein the score S is a number that indicates a likelihood that the input data associated with a given sample belongs to a class of the plural classes.