公开(公告)号：US11185249B2

公开(公告)日：2021-11-30

申请号：US16817454

申请日：2020-03-12

申请人： Hyperfine, Inc.

发明人： Jo Schlemper ,  Seyed Sadegh Moshen Salehi ,  Michal Sofka

IPC分类号： A61B5/055 ,  G01R33/561 ,  G06N3/04 ,  G06N3/08 ,  G06T7/38 ,  G01R33/383 ,  G01R33/44 ,  G01R33/56 ,  G06T3/60 ,  G06T11/00 ,  G16H30/40 ,  G01R33/36 ,  G06T7/262 ,  G06K9/62 ,  G06K9/74 ,  G06T7/00

摘要： Techniques for generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system, the techniques including: obtaining input MR data obtained by imaging the subject using the MRI system; generating a plurality of transformed input MR data instances by applying a respective first plurality of transformations to the input MR data; generating a plurality of MR images from the plurality of transformed input MR data instances and the input MR data using a non-linear MR image reconstruction technique; generating an ensembled MR image from the plurality of MR images at least in part by: applying a second plurality of transformations to the plurality of MR images to obtain a plurality of transformed MR images; and combining the plurality of transformed MR images to obtain the ensembled MR image; and outputting the ensembled MR image.

公开(公告)号：US20220107378A1

公开(公告)日：2022-04-07

申请号：US17496104

申请日：2021-10-07

申请人： Hyperfine, Inc.

发明人： Neel Dey ,  Jo Schlemper ,  Seyed Sadegh Moshen Salehi ,  Michal Sofka ,  Prantik Kundu

IPC分类号： G01R33/56 ,  G06T5/00 ,  G06N3/08 ,  G06N3/04

摘要： Techniques for denoising a magnetic resonance (MR) image are provided, including: obtaining a noisy MR image; denoising the noisy MR image of the subject using a denoising neural network model, and outputting a denoised MR image. The denoising neural network model is trained by: generating first training data for training a first neural network model to denoise MR images by generating a first plurality of noisy MR images using clean MR data associated with a source domain and first MR noise data associated with the target domain; training the first neural network model using the first training data; generating training data for training the denoising neural network model by applying the first neural network model to a second plurality of noisy MR images and generating a plurality of denoised MR images; and training the denoising neural network model using the training data for training the denoising neural network model.

公开(公告)号：US20220015662A1

公开(公告)日：2022-01-20

申请号：US17478127

申请日：2021-09-17

申请人： Hyperfine, Inc.

发明人： Jo Schlemper ,  Seyed Sadegh Moshen Salehi ,  Michal Sofka

IPC分类号： A61B5/055 ,  G16H30/40 ,  G01R33/36 ,  G01R33/383 ,  G01R33/44 ,  G01R33/56 ,  G01R33/561 ,  G06K9/62 ,  G06K9/74 ,  G06N3/04 ,  G06N3/08 ,  G06T3/60 ,  G06T7/00 ,  G06T7/262 ,  G06T7/38 ,  G06T11/00

摘要： Techniques for generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system, the techniques including: obtaining input MR data obtained by imaging the subject using the MRI system; generating a plurality of transformed input MR data instances by applying a respective first plurality of transformations to the input MR data; generating a plurality of MR images from the plurality of transformed input MR data instances and the input MR data using a non-linear MR image reconstruction technique; generating an ensembled MR image from the plurality of MR images at least in part by: applying a second plurality of transformations to the plurality of MR images to obtain a plurality of transformed MR images; and combining the plurality of transformed MR images to obtain the ensembled MR image; and outputting the ensembled MR image.