US 12,142,379 B2
Computing a pathological condition
Markus Butz-Ostendorf, Landsberg am Lech (DE)
Assigned to Labvantage—Biomax GmbH, Planegg (DE)
Appl. No. 17/614,806
Filed by Labvantage-Biomax GmbH, Planegg (DE)
PCT Filed Jun. 3, 2019, PCT No. PCT/EP2019/064373
§ 371(c)(1), (2) Date Nov. 29, 2021,
PCT Pub. No. WO2020/244734, PCT Pub. Date Dec. 10, 2020.
Prior Publication US 2022/0230752 A1, Jul. 21, 2022
Int. Cl. G16H 50/20 (2018.01); G06T 7/00 (2017.01); G06V 10/426 (2022.01); G16H 30/40 (2018.01)
CPC G16H 50/20 (2018.01) [G06T 7/0012 (2013.01); G06V 10/426 (2022.01); G16H 30/40 (2018.01); G06T 2207/20072 (2013.01); G06T 2207/30016 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A computer-implemented method for computing a pathological condition of a subject, said method comprising:
a) obtaining (10) initial cranial image data of a subject from an input interface, and incorporating the initial cranial image data into a knowledge model comprised within a semantic network stored in a memory;
b) performing (12), via a processor, at least one processing sequence on the initial cranial image data using the semantic network to thus provide, in the semantic network, at least one element comprising topographical data of the subject's brain, or a portion of the subject's brain, referenced to a reference coordinate system; wherein the at least one processing sequence performs at least one state iteration of at least a portion of the semantic network from a first state into a second state;
c) comparing (14) the topographical data of the subject's brain to one, or more pathological condition prediction elements of the semantic network to form an indication of a pathological condition of the subject; and
d) generating (16) an additional element in the semantic network comprising the indication of the pathological condition of the subject,
wherein said method further comprises:
generating a subject connectivity graph element of the least one topographical data in the semantic network, wherein the subject connectivity graph element comprises a subject connectivity graph representation of nodes and interconnections between nodes based on functional and/or structural connections between a portion of the subject's brain,
obtaining at least one template connectivity graph element representing a pathological condition, wherein the template connectivity graph element comprises an idealized, averaged, control, or measured template connectivity graph indicative of a brain, or portion of a brain wherein the template connectivity graph is indicative of a neurological condition;
comparing, within the semantic network, portions of the template connectivity graph with corresponding portions of the subject connectivity graph representation;
identifying similarities of the template connectivity graph and the corresponding portions of the subject connectivity graph representation; and
providing the indication of a pathological condition of the subject if the similarities of the template connectivity graph and the corresponding portions of the subject connectivity graph exceed a threshold.