	US 12,190,562 B2
	fMRI task settings with machine learning
Arne Ewald, Hamburg (DE); Rudolf Mathias Johannes Nicolaas Lamerichs, Liempde (NL); Nick Flaschner, Hamburg (DE); Bernhard Gleich, Hamburg (DE); Peter Boernert, Hamburg (DE); Ingmar Graesslin, Boenningstedt (DE); and Johannes Adrianus Overweg, Uelzen (DE)
Assigned to Koninklijke Philips N.V., Eindhoven (NL)
Appl. No. 17/621,718
Filed by KONINKLIJKE PHILIPS N.V., Eindhoven (NL)
PCT Filed Jun. 24, 2020, PCT No. PCT/EP2020/067679 § 371(c)(1), (2) Date Dec. 22, 2021, PCT Pub. No. WO2021/001238, PCT Pub. Date Jan. 7, 2021.
Claims priority of application No. 19183551 (EP), filed on Jul. 1, 2019.
Prior Publication US 2022/0237787 A1, Jul. 28, 2022
Int. Cl. G06V 10/764 (2022.01); G06N 3/08 (2023.01); G06T 7/00 (2017.01); G06V 10/82 (2022.01)

CPC G06V 10/764 (2022.01) [G06N 3/08 (2013.01); G06T 7/0012 (2013.01); G06V 10/82 (2022.01); G06T 2207/10088 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)]

19 Claims

1. A medical imaging system comprising:

a magnetic resonance imaging (MRI) system configured to acquire functional magnetic resonance imaging (fMRI) data from a subject within an imaging zone;

a memory configured to store machine executable instructions;

a processor configured to control the medical imaging system, wherein execution of the machine executable instructions causes the processor to:

receive a set of predefined subject data descriptive of the subject comprising values of a set of predefined subject parameters, wherein a subject parameter of the set of subject parameters indicates at least one of an age, disease, gender, handedness or body size of the subject;

in response to inputting the set of subject data into a trained deep neural network (DNN), receive from the trained DNN a predicted task;

present the task to the subject; and

control the MRI system for acquiring fMRI data from the subject in response to the predicted task being performed by the subject during the acquisition.