公开(公告)号：US20240177459A1

公开(公告)日：2024-05-30

申请号：US18059082

申请日：2022-11-28

Applicant: GE Precision Healthcare LLC

Inventor： Rahul Venkataramani ,  Vikram Reddy Melapudi

IPC: G06V10/774 ,  G06T7/00 ,  G06V10/82

CPC classification number: G06V10/774 ,  G06T7/0014 ,  G06V10/82 ,  G06V2201/03

Abstract: Systems/techniques that facilitate variable confidence machine learning are provided. In various embodiments, a system can access a medical image. In various aspects, the system can perform, via execution of a machine learning model, a regression task on the medical image, wherein the machine learning model can receive as input both the medical image and a user-specified confidence indicator.

公开(公告)号：US20230200778A1

公开(公告)日：2023-06-29

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 ,  G06N5/04 ,  G06N5/02

CPC classification number: A61B8/4254 ,  A61B8/463 ,  G06N5/04 ,  G06N5/022

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：US20230025182A1

公开(公告)日：2023-01-26

申请号：US17381113

申请日：2021-07-20

Applicant: GE Precision Healthcare LLC

Inventor： Rahul Venkataramani ,  Vikram Melapudi

IPC: G06T7/00 ,  A61B8/00

Abstract: Methods and systems are provided for dynamically selecting ultrasound transmits. In one example, a method includes dynamically updating a number of transmit lines and/or a pattern of transmit lines for acquiring an ultrasound image based on a prior ultrasound image and a task to be performed with the ultrasound image, and acquiring the ultrasound image with an ultrasound probe controlled to operate with the updated number of transmit lines and/or the updated pattern of transmit lines.

公开(公告)号：US20220160334A1

公开(公告)日：2022-05-26

申请号：US17101149

申请日：2020-11-23

Applicant: GE Precision Healthcare LLC

Inventor： Rahul Venkataramani ,  Dani Pinkovich

IPC: A61B8/08 ,  A61B8/00

Abstract: A system and method for enhancing visualization of a pleural line by automatically detecting and marking the pleural line in images of an ultrasound scan is provided. The method includes receiving an ultrasound cine loop acquired according to a first mode. The method includes processing the ultrasound cine loop according to the first mode. The method includes processing at least a portion of the ultrasound cine loop according to a second mode. The method includes identifying a position of an anatomical structure based on the at least a portion of the ultrasound cine loop processed according to the second mode. The method includes displaying, at a display system, the position of the anatomical structure on a first mode image generated from the ultrasound cine loop processed according to the first mode.

公开(公告)号：US20250156709A1

公开(公告)日：2025-05-15

申请号：US18942209

申请日：2024-11-08

Applicant: GE Precision Healthcare LLC

Inventor： Rahul Venkataramani ,  Prasad Sudhakara Murthy ,  Rachana Sathish ,  KS Shriram

IPC: G06N3/08 ,  G06N3/045

Abstract: Methods and systems are provided for a customizable deep learning system. In one example, a system includes a processor and non-transitory memory storing instructions executable by the processor to receive a user selection of a time budget, enter an input to a deep learning system, the deep learning system including one or more deep learning models configured to generate a plurality of outputs based on the input, and wherein a number of outputs included in the plurality of outputs is based on the time budget, combine the plurality of outputs to form a final output, and output the final output for display on a display device, for downstream processing, and/or for storage in memory.

公开(公告)号：US12059296B2

公开(公告)日：2024-08-13

申请号：US17143586

申请日：2021-01-07

Applicant: GE Precision Healthcare LLC

Inventor： Rahul Venkataramani ,  Vikram Melapudi ,  Pavan Annangi

IPC: A61B8/00 ,  A61B8/08 ,  A61B34/20

CPC classification number: A61B8/4263 ,  A61B8/466 ,  A61B8/483 ,  A61B8/488 ,  A61B34/20 ,  A61B2034/2063

Abstract: Systems, machine-readable media, and methods for ultrasound imaging can include acquiring three-dimensional data for one or more patient data sets and generating a three-dimensional environment based on one or more transition areas identified between a plurality of volumes of the three-dimensional data. A method can also include generating a set of probe guidance instructions based at least in part on the one or more transition areas and the plurality of volumes of the three-dimensional data, and acquiring, using an ultrasound probe, a first frame of two-dimensional data for a patient. The method can also include executing the set of probe guidance instructions to provide probe feedback for acquiring at least a second frame of two-dimensional data.

公开(公告)号：US11972584B2

公开(公告)日：2024-04-30

申请号：US17488750

申请日：2021-09-29

Applicant: GE Precision Healthcare LLC

Inventor： Rahul Venkataramani ,  Krishna Seetharam Shriram ,  Aditi Garg

IPC: G06T7/40 ,  G06T7/11

CPC classification number: G06T7/40 ,  G06T7/11 ,  G06T2207/10132 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30061 ,  G06T2207/30084

Abstract: Systems and methods for tissue specific time gain compensation of an ultrasound image are provided. The method comprises acquiring an ultrasound image of a subject and displaying the ultrasound image over a console. The method further comprises selecting by a user a region within the ultrasound image that requires time gain compensation. The method further comprises carrying out time gain compensation of the user selected region of the ultrasound image. The method further comprises identifying a region having a similar texture to the user selected region and carrying out time gain compensation of the user selected region by an artificial intelligence (AI) based deep learning module.

公开(公告)号：US20230409673A1

公开(公告)日：2023-12-21

申请号：US17807761

申请日：2022-06-20

Applicant: GE Precision Healthcare LLC

Inventor： Ravishankar Hariharan ,  Rohan Keshav Patil ,  Rahul Venkataramani ,  Prasad Sudhakara Murthy ,  Deepa Anand ,  Utkarsh Agrawal

IPC: G06K9/62 ,  G06N3/02

CPC classification number: G06K9/6265 ,  G06K9/6227 ,  G06N3/02

Abstract: Systems/techniques that facilitate improved uncertainty scoring for neural networks via stochastic weight perturbations are provided. In various embodiments, a system can access a trained neural network and/or a data candidate on which the trained neural network is to be executed. In various aspects, the system can generate an uncertainty indicator representing how confidently executable or how unconfidently executable the trained neural network is with respect to the data candidate, based on a set of perturbed instantiations of the trained neural network.

公开(公告)号：US20230052078A1

公开(公告)日：2023-02-16

申请号：US17889201

申请日：2022-08-16

Applicant: GE Precision Healthcare LLC

Inventor： Pavan Annangi ,  Deepa Anand ,  Bhushan Patil ,  Rahul Venkataramani

IPC: G06V10/778 ,  G06V10/20 ,  G06V10/26 ,  G16H30/40

Abstract: Systems and methods for self-supervised representation learning as a means to generate context-specific pretrained models include selecting data from a set of available data sets; selecting a pretext task from domain specific pretext tasks; selecting a target problem specific network architecture based on a user selection from available choices or any customized model as per user preference; and generating a pretrained model for the selected network architecture using the selected data obtained from the set of available data sets and a pretext task as obtained from domain specific pretext tasks.

公开(公告)号：US11580384B2

公开(公告)日：2023-02-14

申请号：US16522367

申请日：2019-07-25

Applicant: GE Precision Healthcare LLC

Inventor： Rahul Venkataramani ,  Sai Hareesh Anamandra ,  Hariharan Ravishankar ,  Prasad Sudhakar

IPC: G06N3/08 ,  G06T7/00 ,  G06N3/04

Abstract: The present approach relates to a system capable of life-long learning in a deep learning context. The system includes a deep learning network configured to process an input dataset and perform one or more tasks from among a first set of tasks. As an example, the deep learning network may be part of an imaging system, such as a medical imaging system, or may be used in industrial applications. The system further includes a learning unit communicatively coupled to the deep learning network 102 and configured to modify the deep learning network so as to enable it to perform one or more tasks in a second task list without losing the ability to perform the tasks from the first list.