公开(公告)号：US20250046057A1

公开(公告)日：2025-02-06

申请号：US18364101

申请日：2023-08-02

Applicant: GE Precision Healthcare LLC

Inventor： Rahul Venkataramani ,  Rachana Sathish ,  Krishna Seetharam Shriram ,  Chandan Kumar Mallappa Aladahalli ,  Christian Fritz Perrey ,  Michaela Hofbauer

IPC: G06V10/764 ,  G06T7/00 ,  G06T7/11 ,  G06V10/82

Abstract: A method for analyzing uncertainty in a multi-scale interpretation of a medical image includes inputting the medical image into a trained segmentation network. The method includes outputting via the trained segmentation network a segmentation output mask for each pixel of the medical image or a region of interest of the medical image. The method includes utilizing a deterministic function to aggregate segmentation output masks for all pixels of the medical image or the region of interest and to output a first classification prediction of the aggregated segmentation output masks. The method includes inputting the medical image into a trained classification network. The method includes outputting a second classification prediction of the medical image or the region of interest. The method includes determining an uncertainty between the first classification prediction and the second classification prediction via comparison of the first classification prediction to the second classification prediction.

公开(公告)号：US12193882B2

公开(公告)日：2025-01-14

申请号：US17209080

申请日：2021-03-22

Applicant: GE Precision Healthcare LLC

Inventor： Chandan Kumar Mallappa Aladahalli ,  Krishna Seetharam Shriram ,  Vikram Melapudi

IPC: A61B8/00 ,  A61B8/08 ,  G06T7/10

Abstract: Methods and systems are provided for generating user guidance for ultrasound imaging. In one example, a method includes determining, with a probe recommendation model, a user action to an ultrasound probe prior to and/or during acquisition of a current ultrasound image frame, one or more anatomical features in the current ultrasound image frame, and an anatomy view of the current ultrasound image frame, and outputting, for display on a display device, a probe motion recommendation based on the user action, the one or more anatomical features, and the anatomy view.

公开(公告)号：US20240078669A1

公开(公告)日：2024-03-07

申请号：US18497912

申请日：2023-10-30

Applicant: GE Precision Healthcare LLC

Inventor： Tao Tan ,  Máté Fejes ,  Gopal Avinash ,  Ravi Soni ,  Bipul Das ,  Rakesh Mullick ,  Pál Tegzes ,  Lehel Ferenczi ,  Vikram Melapudi ,  Krishna Seetharam Shriram

IPC: G06T7/00 ,  G06N3/08 ,  G06T15/08

CPC classification number: G06T7/0012 ,  G06N3/08 ,  G06T15/08 ,  G06T2207/10088 ,  G06T2207/10104

Abstract: Methods and systems are provided for inferring thickness and volume of one or more object classes of interest in two-dimensional (2D) medical images, using deep neural networks. In an exemplary embodiment, a thickness of an object class of interest may be inferred by acquiring a 2D medical image, extracting features from the 2D medical image, mapping the features to a segmentation mask for an object class of interest using a first convolutional neural network (CNN), mapping the features to a thickness mask for the object class of interest using a second CNN, wherein the thickness mask indicates a thickness of the object class of interest at each pixel of a plurality of pixels of the 2D medical image; and determining a volume of the object class of interest based on the thickness mask and the segmentation mask.

公开(公告)号：US11810294B2

公开(公告)日：2023-11-07

申请号：US17214026

申请日：2021-03-26

Applicant: GE Precision Healthcare LLC

Inventor： Krishna Seetharam Shriram ,  Chandan Kumar Aladahalli ,  Vikram Melapudi

IPC: G06T7/00 ,  A61B8/00 ,  A61B8/08 ,  G06F3/14 ,  G06N3/08 ,  G06T7/11

CPC classification number: G06T7/0012 ,  A61B8/4444 ,  A61B8/463 ,  A61B8/5207 ,  G06F3/14 ,  G06N3/08 ,  G06T7/11 ,  G06T2207/10132 ,  G06T2207/20021 ,  G06T2207/20084

Abstract: Various methods and systems are provided for individually analyzing a plurality of subregions within an ultrasound image for acoustic shadowing. In one embodiment, a method includes acquiring ultrasound data along a plurality of receive lines, generating an ultrasound image based on the ultrasound data, dividing the ultrasound image into a plurality of subregions, and individually analyzing each of the plurality of subregions for acoustic shadowing. The method includes detecting acoustic shadowing in one or more of the plurality of subregions, displaying the ultrasound image, and graphically indicating the one or more of the plurality of subregions in which the acoustic shadowing was detected on the ultrasound image while the ultrasound image is displayed on a display device.

公开(公告)号：US20230260142A1

公开(公告)日：2023-08-17

申请号：US17648696

申请日：2022-01-24

Applicant: GE Precision Healthcare LLC

Inventor： Sudhanya Chatterjee ,  Dattesh Dayanand Shanbhag ,  Krishna Seetharam Shriram

IPC: G06T7/33

CPC classification number: G06T7/344 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Systems/techniques that facilitate multi-modal image registration via modality-neutral machine learning transformation are provided. In various embodiments, a system can access a first image and a second image, where the first image can depict an anatomical structure according to a first imaging modality, and where the second image can depict the anatomical structure according to a second imaging modality that is different from the first imaging modality. In various aspects, the system can generate, via execution of a machine learning model on the first image and the second image, a modality-neutral version of the first image and a modality-neutral version of the second image. In various instances, the system can register the first image with the second image, based on the modality-neutral version of the first image and the modality-neutral version of the second image.

公开(公告)号：US11727086B2

公开(公告)日：2023-08-15

申请号：US17093960

申请日：2020-11-10

Applicant: GE Precision Healthcare LLC

Inventor： Tao Tan ,  Gopal B. Avinash ,  Máté Fejes ,  Ravi Soni ,  Dániel Attila Szabó ,  Rakesh Mullick ,  Vikram Melapudi ,  Krishna Seetharam Shriram ,  Sohan Rashmi Ranjan ,  Bipul Das ,  Utkarsh Agrawal ,  László Ruskó ,  Zita Herczeg ,  Barbara Darázs

IPC: G06F18/214 ,  G06T7/30 ,  G06N5/04 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/50 ,  A61B6/03 ,  A61B6/00 ,  A61B5/055 ,  A61B5/00 ,  G06T5/50 ,  G06F18/22 ,  G06F18/28 ,  G06F18/21

CPC classification number: G06F18/214 ,  A61B5/055 ,  A61B5/7267 ,  A61B6/032 ,  A61B6/5223 ,  G06F18/2178 ,  G06F18/22 ,  G06F18/28 ,  G06N5/04 ,  G06T5/50 ,  G06T7/30 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/50 ,  G06T2200/04 ,  G06T2207/10081 ,  G06T2207/10116 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20212 ,  G06T2207/30004 ,  G06V2201/03

Abstract: Techniques are described for generating mono-modality training image data from multi-modality image data and using the mono-modality training image data to train and develop mono-modality image inferencing models. A method embodiment comprises generating, by a system comprising a processor, a synthetic 2D image from a 3D image of a first capture modality, wherein the synthetic 2D image corresponds to a 2D version of the 3D image in a second capture modality, and wherein the 3D image and the synthetic 2D image depict a same anatomical region of a same patient. The method further comprises transferring, by the system, ground truth data for the 3D image to the synthetic 2D image. In some embodiments, the method further comprises employing the synthetic 2D image to facilitate transfer of the ground truth data to a native 2D image captured of the same anatomical region of the same patient using the second capture modality.

公开(公告)号：US20220309649A1

公开(公告)日：2022-09-29

申请号：US17214026

申请日：2021-03-26

Applicant: GE Precision Healthcare LLC

Inventor： Krishna Seetharam Shriram ,  Chandan Kumar Aladahalli ,  Vikram Melapudi

IPC: G06T7/00 ,  A61B8/00 ,  A61B8/08 ,  G06T7/11 ,  G06F3/14 ,  G06N3/08

Abstract: Various methods and systems are provided for individually analyzing a plurality of subregions within an ultrasound image for acoustic shadowing. In one embodiment, a method includes acquiring ultrasound data along a plurality of receive lines, generating an ultrasound image based on the ultrasound data, dividing the ultrasound image into a plurality of subregions, and individually analyzing each of the plurality of subregions for acoustic shadowing. The method includes detecting acoustic shadowing in one or more of the plurality of subregions, displaying the ultrasound image, and graphically indicating the one or more of the plurality of subregions in which the acoustic shadowing was detected on the ultrasound image while the ultrasound image is displayed on a display device.

公开(公告)号：US20220284570A1

公开(公告)日：2022-09-08

申请号：US17192804

申请日：2021-03-04

Applicant: GE Precision Healthcare LLC

Inventor： Tao Tan ,  Máté Fejes ,  Gopal Avinash ,  Ravi Soni ,  Bipul Das ,  Rakesh Mullick ,  Pál Tegzes ,  Lehel Ferenczi ,  Vikram Melapudi ,  Krishna Seetharam Shriram

IPC: G06T7/00 ,  G06N3/08 ,  G06T15/08

Abstract: Methods and systems are provided for inferring thickness and volume of one or more object classes of interest in two-dimensional (2D) medical images, using deep neural networks. In an exemplary embodiment, a thickness of an object class of interest may be inferred by acquiring a 2D medical image, extracting features from the 2D medical image, mapping the features to a segmentation mask for an object class of interest using a first convolutional neural network (CNN), mapping the features to a thickness mask for the object class of interest using a second CNN, wherein the thickness mask indicates a thickness of the object class of interest at each pixel of a plurality of pixels of the 2D medical image; and determining a volume of the object class of interest based on the thickness mask and the segmentation mask.

公开(公告)号：US20220067919A1

公开(公告)日：2022-03-03

申请号：US17003467

申请日：2020-08-26

Applicant: GE Precision Healthcare LLC

Inventor： Krishna Seetharam Shriram ,  Arathi Sreekumari ,  Rakesh Mullick

IPC: G06T7/00 ,  G06K9/32 ,  G06T11/00

Abstract: The present disclosure relates to a system and method for identifying a tumor or lesion in a probability map. In accordance with certain embodiments, a method includes identifying, with a processor, a first region of interest in a first projection image, generating, with the processor, a first probability map from the first projection image and a second probability map from a second projection image, wherein the first probability map includes a second region of interest that has location that corresponds to a location of the first region of interest, interpolating the first probability map and the second probability map, thereby generating a probability volume, wherein the probability volume includes the second region of interest, and outputting, with the processor, a representation of the probability volume to a display.

公开(公告)号：US20210145411A1

公开(公告)日：2021-05-20

申请号：US16687392

申请日：2019-11-18

Applicant: GE Precision Healthcare LLC

Inventor： Chandan Kumar Mallappa Aladahalli ,  Krishna Seetharam Shriram ,  Vikram Melapudi

IPC: A61B8/08 ,  A61B8/00 ,  G06T7/194

Abstract: Methods and systems are provided for turbulence monitoring during ultrasound scanning. In one example, during scanning with an ultrasound probe, a turbulence amount between two successive frames may be monitored, and in response to the turbulence amount at or above the higher threshold, deployment of the one or more image interpretation protocols may be stopped or delayed until the turbulence amount decreases below the higher threshold.