US 12,079,989 B2
Identifying boundaries of lesions within image data
Dimitrios Mavroeidis, Utrecht (NL); Stojan Trajanovski, London (GB); and Bart Jacob Bakker, Eindhoven (NL)
Assigned to KONINKLIJKE PHILIPS N.V., Eindhoven (NL)
Appl. No. 17/600,405
Filed by KONINKLIJKE PHILIPS N.V., Eindhoven (NL)
PCT Filed Apr. 3, 2020, PCT No. PCT/EP2020/059583
§ 371(c)(1), (2) Date Sep. 30, 2021,
PCT Pub. No. WO2020/201516, PCT Pub. Date Oct. 8, 2020.
Claims priority of application No. 19167213 (EP), filed on Apr. 4, 2019.
Prior Publication US 2022/0180516 A1, Jun. 9, 2022
Int. Cl. G06T 7/00 (2017.01); G06T 7/12 (2017.01); G06T 7/187 (2017.01); G06T 7/70 (2017.01); G06V 10/70 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01)
CPC G06T 7/0012 (2013.01) [G06T 7/12 (2017.01); G06T 7/187 (2017.01); G06T 7/70 (2017.01); G06V 10/70 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20092 (2013.01); G06T 2207/30096 (2013.01)] 20 Claims
OG exemplary drawing
 
16. A method implemented by a processing system, the method comprising:
receiving, by the processing system, N-dimensional medical image data, comprising a plurality of image data points;
generating, by the processing system:
N-dimensional probability data, comprising probability data points respective to the image data points in the plurality, wherein the probability data points indicate a probability that the image data points are part of a lesion; and
N-dimensional uncertainty data, comprising uncertainty data points respective to the probability data points in the plurality; and
identifying, by the processing system, one or more boundaries of lesions in the medical image data using at least the probability data points and the uncertainty data points.