TY - PAT
T1 - Apparatus and method for producing three-dimensional models from magnetic resonance imaging
AU - Sutton, Brad
AU - Bramlet, Matthew
AU - Peng, Xi
AU - Urbain, Kevin
PY - 2022/8/23
Y1 - 2022/8/23
N2 - Aspects of the subject disclosure may include, for example, a method comprising: receiving, by a processing system including a processor, an input three-dimensional dataset comprising a first plurality of two-dimensional images of all or a portion of a subject; applying, by the processing system, bias field correction to the input three-dimensional dataset to generate a corrected three-dimensional dataset comprising a second plurality of two-dimensional images; and generating, by the processing system, a labeled three-dimensional dataset comprising a third plurality of two-dimensional images, wherein the labeled three-dimensional dataset further comprises one or more labels indicating an anatomical structure, and wherein the labeled three-dimensional dataset is generated via a convolutional neural network based upon the corrected three-dimensional dataset and based upon a previously trained three-dimensional dataset. Additional embodiments are disclosed.
AB - Aspects of the subject disclosure may include, for example, a method comprising: receiving, by a processing system including a processor, an input three-dimensional dataset comprising a first plurality of two-dimensional images of all or a portion of a subject; applying, by the processing system, bias field correction to the input three-dimensional dataset to generate a corrected three-dimensional dataset comprising a second plurality of two-dimensional images; and generating, by the processing system, a labeled three-dimensional dataset comprising a third plurality of two-dimensional images, wherein the labeled three-dimensional dataset further comprises one or more labels indicating an anatomical structure, and wherein the labeled three-dimensional dataset is generated via a convolutional neural network based upon the corrected three-dimensional dataset and based upon a previously trained three-dimensional dataset. Additional embodiments are disclosed.
M3 - Patent
M1 - 11423603
Y2 - 2020/12/17
ER -