公开(公告)号：US20220319006A1

公开(公告)日：2022-10-06

申请号：US17220770

申请日：2021-04-01

Applicant: GE Precision Healthcare LLC

Inventor： Pavan Annangi ,  Rahul Venkataramani ,  Deepa Anand ,  Eigil Samset

IPC: G06T7/00 ,  A61B8/08 ,  G06K9/62 ,  G06K9/03 ,  G06K9/32 ,  G06N3/04 ,  G06N3/08

Abstract: Various methods and systems are provided for bicuspid valve detection with ultrasound imaging. In one embodiment, a method comprises acquiring ultrasound video of a heart over at least one cardiac cycle, identifying frames in the ultrasound video corresponding to at least one cardiac phase, and classifying a cardiac structure in the identified frames as a bicuspid valve or a tricuspid valve. A generative model such as a variational autoencoder trained on ultrasound image frames at the at least one cardiac phase may be used to classify the cardiac structure. In this way, relatively rare occurrences of bicuspid aortic valves may be automatically detected during regular cardiac ultrasound screenings.

公开(公告)号：US20210350531A1

公开(公告)日：2021-11-11

申请号：US17242156

申请日：2021-04-27

Applicant: GE Precision Healthcare LLC

Inventor： Vikram Melapudi ,  Rahul Venkataramani

IPC: G06T7/00 ,  A61B8/00 ,  A61B8/08 ,  G06N3/08

Abstract: Systems, methods and computer program products are provided to collect ultrasound (US) data. A processor is configured to acquire the US data along one or more acquisition scan planes. The US data defines a plurality of image frames that have a first image quality. The processor is further configured to apply a generative model to at least one of the US data or plurality of image frames to generate a synthetic scan plane image along a synthetic scan plane. The generative model is defined based on one or more training ultrasound data sets. The synthetic scan plane image has an image quality that is common with the first image quality of the plurality of image frames. The system further comprises a display configured to display the synthetic scan plane image.

公开(公告)号：US20250149169A1

公开(公告)日：2025-05-08

申请号：US18504649

申请日：2023-11-08

Applicant: GE Precision Healthcare LLC

Inventor： Deepa Anand ,  Dattesh Shanbhag ,  Hariharan Ravishankar ,  Suresh Emmanuel Devadoss Joel ,  Rakesh Mullick ,  Rachana Sathish ,  Rahul Venkataramani ,  Krishna Seetharam Shriram ,  Prasad Sudhakara Murthy

IPC: G16H50/20 ,  G06T7/00 ,  G16H30/40

Abstract: Systems or techniques for facilitating learnable visual prompt engineering are provided. In various embodiments, a system can access a medical image and a pre-trained machine learning model that is configured to perform a diagnostic or prognostic inferencing task. In various aspects, the system can apply a pre-processing transformation to one or more pixels or voxels of the medical image, thereby yielding a transformed version of the medical image, wherein the pre-processing transformation can convert an input pixel or voxel intensity value to an output pixel or voxel intensity value via one or more parameters that are iteratively learned. In various instances, the system can perform the diagnostic or prognostic inferencing task, by executing the pre-trained machine learning model on the transformed version of the medical image.

公开(公告)号：US20250124569A1

公开(公告)日：2025-04-17

申请号：US18486038

申请日：2023-10-12

Applicant: GE Precision Healthcare LLC

Inventor： KS Shriram ,  Rahul Venkataramani ,  Chandan Kumar Aladahalli ,  Stephan Anzengruber

IPC: G06T7/00 ,  G06T7/174 ,  G06T7/60 ,  G06T7/70 ,  G06V40/10

Abstract: Methods and systems are provided for identifying a mid-sagittal plane (MSP) in a medical image. In one example, a method for an image processing system comprises obtaining an input volume acquired with an ultrasound imaging system, entering the input volume as input to a segmentation model trained to output a segmentation mask that identifies a segmented fetal head, a first segmented orbit, and a second segmented orbit, identifying a mid-sagittal plane (MSP) of the fetal head using the segmented first orbit and the segmented second orbit, visually displaying the MSP on the segmented fetal head, in response to determining the MSP is not an acquired plane, alerting a user of poor facial rendering or a possibility of poor facial rendering and prompting the user to reorient an ultrasound probe and reacquire the input volume, and displaying the input volume and/or saving the input volume in memory.

公开(公告)号：US12239484B2

公开(公告)日：2025-03-04

申请号：US17646085

申请日：2021-12-27

Applicant: GE Precision Healthcare LLC

Inventor： Rahul Venkataramani ,  Chandan Aladahalli ,  Krishna Seetharam Shriram ,  Vikram Melapudi

IPC: A61B8/00 ,  G06V10/82

Abstract: Methods and systems are provided for generating ultrasound probe motion recommendations. In one example, a method includes obtaining an ultrasound image of a source scan plane, the ultrasound image acquired with an ultrasound probe at a first location relative to a patient, entering the ultrasound image as input to a probe recommendation model trained to output a set of recommendations to move the ultrasound probe from the first location to a plurality of additional locations at which a plurality of target scan planes can be imaged, and displaying the set of recommendations on a display device.

公开(公告)号：US12229685B2

公开(公告)日：2025-02-18

申请号：US17155997

申请日：2021-01-22

Applicant: GE Precision Healthcare LLC

Inventor： Hariharan Ravishankar ,  Rahul Venkataramani ,  Prasad Sudhakara Murthy ,  Annangi P. Pavan Kumar

IPC: G06N3/088 ,  G06N3/045

Abstract: Systems/techniques that facilitate generation of model suitability coefficients are provided. In various embodiments, a system can access a model trained on a training dataset, and the system can compute a coefficient indicating whether the model is suitable for deployment on a target dataset, based on analyzing activation maps associated with the model. In some cases, the system can: train a generative adversarial network (GAN) to learn a distribution of training activation maps produced by the model; generate a set of target activation maps of the model, by feeding samples from the target dataset to the model; cause a generator of the GAN to generate synthetic training activation maps from the learned distribution of training activation maps; iteratively perturb inputs of the generator until distances between the synthetic training activation maps and the target activation maps are minimized; and aggregate the minimized distances to form the coefficient.

公开(公告)号：US12056871B2

公开(公告)日：2024-08-06

申请号：US17242156

申请日：2021-04-27

Applicant: GE Precision Healthcare LLC

Inventor： Vikram Melapudi ,  Rahul Venkataramani

IPC: A61B8/08 ,  A61B8/00 ,  G06N3/08 ,  G06T7/00

CPC classification number: G06T7/0012 ,  A61B8/461 ,  A61B8/5269 ,  G06N3/08 ,  G06T2207/10132

Abstract: Systems, methods and computer program products are provided to collect ultrasound (US) data. A processor is configured to acquire the US data along one or more acquisition scan planes. The US data defines a plurality of image frames that have a first image quality. The processor is further configured to apply a generative model to at least one of the US data or plurality of image frames to generate a synthetic scan plane image along a synthetic scan plane. The generative model is defined based on one or more training ultrasound data sets. The synthetic scan plane image has an image quality that is common with the first image quality of the plurality of image frames. The system further comprises a display configured to display the synthetic scan plane image.

公开(公告)号：US20240104718A1

公开(公告)日：2024-03-28

申请号：US17933322

申请日：2022-09-19

Applicant: GE Precision Healthcare LLC

Inventor： Rahul Venkataramani ,  Vikram Reddy Melapudi ,  Prasad Sudhakara Murthy

IPC: G06T7/00 ,  G06N3/04 ,  G06N3/08 ,  G16H30/40

CPC classification number: G06T7/0012 ,  G06N3/04 ,  G06N3/08 ,  G16H30/40 ,  G06T2200/24 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30004

Abstract: Systems/techniques that facilitate machine learning image analysis based on explicit equipment parameters are provided. In various embodiments, a system can access a medical image generated by a medical imaging device. In various instances, the system can perform, via execution of a machine learning model, an inferencing task on the medical image. In various cases, the machine learning model can receive as input the medical image and a set of equipment parameters. In various aspects, the set of equipment parameters can indicate how the medical imaging device was configured to generate the medical image.

公开(公告)号：US20230267618A1

公开(公告)日：2023-08-24

申请号：US17651770

申请日：2022-02-18

Applicant: GE Precision Healthcare LLC

Inventor： Anuprriya Gogna ,  Vikram Melapudi ,  Rahul Venkataramani

IPC: G06T7/12 ,  G06T11/00 ,  G06T7/00 ,  A61B8/08 ,  A61B8/00 ,  G16H30/40

CPC classification number: G06T7/12 ,  G06T11/00 ,  G06T7/0012 ,  A61B8/08 ,  A61B8/463 ,  A61B8/523 ,  G16H30/40 ,  G06T2207/10136 ,  G06T2207/20081 ,  G06T2207/30004

Abstract: Methods and systems are provided for an automated ultrasound exam. In one example, a method includes identifying a view plane of interest based on one or more 3D ultrasound images, obtaining a view plane image including the view plane of interest from a 3D volume of ultrasound data of a patient, where the one or more 3D ultrasound images are generated from the 3D volume of ultrasound data, segmenting an anatomical region of interest (ROI) within the view plane image to generate a contour of the anatomical ROI, and displaying the contour on the view plane image.

公开(公告)号：US11593933B2

公开(公告)日：2023-02-28

申请号：US16819966

申请日：2020-03-16

Applicant: GE Precision Healthcare LLC

Inventor： Krishna Seetharam Shriram ,  Rahul Venkataramani ,  Aditi Garg ,  Chandan Kumar Mallappa Aladahalli

IPC: G06T7/00 ,  A61B8/00 ,  G06T7/11 ,  G06T7/73

Abstract: Methods and systems are provided for assessing image quality of ultrasound images. In one example, a method includes determining a probe position quality parameter of an ultrasound image, the probe position quality parameter representative of a level of quality of the ultrasound image with respect to a position of an ultrasound probe used to acquire the ultrasound image, determining one or more acquisition settings quality parameters of the ultrasound image, each acquisition settings quality parameter representative of a respective level of quality of the ultrasound image with respect to a respective acquisition setting used to acquire the ultrasound image, and providing feedback to a user of the ultrasound system based on the probe position quality parameter and/or the one or more acquisition settings quality parameters, the probe position quality parameter and each acquisition settings quality parameter determined based on output from separate image quality assessment models.