General Electric Company

Ge Precision Healthcare LLC

Ge Medical Systems Global Technology Company, LLC

Razvan Iordache

Serge Muller

Serge Louis Wilfrid Muller

Sylvain Bernard

Giovanni Palma

Ann-Katherine Carton

Giovanni John Jacques Palma

Remy Klausz

Laurence Vancamberg

Gero L Peters

Henri Souchay

Sylvie Puong

Jorge Corsino Espino

Zhijin Li

Bernhard Erich Hermann Claus

Aurelie Boudier

Xin Wang

Cynthia Elizabeth Landberg Davis

Pablo Milioni De Carvalho

Aurélie Boudier

Fanny Jeunehomme

Virginie Alexandra Corre

Marco Blumenthal

Serge Calisti

Xavier Bouchevreau

Bruno Le Corgne

Axel Crasemann

Ronald N Blaski

Charlotte Delmas

Rémy Klausz

Sylvie Saab-Puong

Ann-katherine Carton

Jérôme Sutty

Clarisse Dromain

Aurëlie Boudier

Pierre Tudal

Jerome Sutty

Jose Abellan-Martinez

Pablo Milioni DeCarvalho

Ibrahima Faye

Virginie Corre

The current disclosure provides for mapping medical images to style transferred medical images using deep neural networks, while maintaining clinical quality of the style transferred medical image, thereby enabling a clinician to evaluate medical images in a preferred style without loss of clinically relevant content. In one embodiment the current disclosure provides for a method comprising, acquiring a medical image of an anatomical region of a subject, wherein the medical image is in a first style, selecting a target style, wherein the target style is distinct from the first style, selecting a clinical quality metric, selecting a trained style transfer network based on the target style and the clinical quality metric, mapping the medical image to a style transferred medical image using the trained style transfer network, wherein the style transferred medical image is in the target style, and displaying the style transferred medical image via a display device.

Systems and methods for medical image style transfer using deep neural networks

An imaging system, such as a DBT system, capable of providing an operator of the system with information concerning the location, magnitude and direction of motion detected by the system during performance of the scan to enhance image processing. The imaging system provides the motion information to the operator directly in conjunction with the images processed by the imaging system thereby providing the operator with sufficient information for decisions regarding the need for additional images for completing the scan with the imaging system before the patient is discharged, or even before the breast is decompressed.

Method and system for motion assessment and correction in digital breast tomosynthesis

Methods and systems for deep learning based image reconstruction are disclosed herein. An example method includes receiving a set of imaging projections data, identifying a voxel to reconstruct, receiving a trained regression model, and reconstructing the voxel. The voxel is reconstructed by: projecting the voxel on each imaging projection in the set of imaging projections according to an acquisition geometry, extracting adjacent pixels around each projected voxel, feeding the regression model with the extracted adjacent pixel data to produce a reconstructed value of the voxel, and repeating the reconstruction for each voxel to be reconstructed to produce a reconstructed image.

Systems and methods for deep learning-based image reconstruction

Methods and systems are provided for reconstruction error assessment for an interventional tool utilized in an image guided interventional procedure. In one example, an error model based on a target lesion position within a tissue, one or more interventional tool parameters, and imaging system parameters may be utilized to estimate an expected reconstruction error for the interventional tool. In another example, when the interventional tool is within the tissue, the expected reconstruction error may be utilized along with observed tool shape and size to infer an actual tool position and shape within the tissue.

Methods and systems for biopsy needle reconstruction error assessment

An apparatus for controlling medical equipment is provided. The apparatus includes patient positioning equipment, and a control system coupled to the patient positioning equipment. The control system is configured to control a function of the medical equipment.

Apparatus, system and method for controlling medical equipment

A system for imaging biopsy samples obtained from a patient includes: a radiation source; a radiation detector having a surface that defines a first imaging region, a second imaging region, and a third imaging region; and a collimator having a body defining an opening and selectively adjustable between a first imaging position and a second imaging position. The first imaging position allows radiation rays to pass from the radiation source, through the opening, and into the second imaging region while restricting the radiation rays from passing into the first imaging region when the radiation source is in a first scanning position. The second imaging position allows radiation rays to pass from the radiation source, through the opening, and into the third imaging region while restricting the radiation rays from passing into the first imaging region when the radiation source is in a second scanning position.

System and method for imaging biopsy samples obtained from a patient

An imaging system, such as a DBT system, is provided that is capable of providing processing of an image from initial generation/reconstruction of the image through the review of the image by a radiologist or other practitioner that produces images optimized for the particular task/process performed using the images. The task/review that the radiologist is performing on the processed or reconstructed image can be modeled with regard to the initial generation of the processed or reconstructed images from the raw images or the model considerations can be retroactively applied and back propagated through the image processing performed by the system. These modeling considerations that can take the form of an indicator of clinical performance is/are used by the system to optimize and produce an image(s) that best represents the items in the image necessary for an accurate diagnosis of the patient when reviewed by the radiologist.

Clinical task-based processing of images

A mammography apparatus includes a support plate for supporting a breast of a patient, a compression plate movable toward and away from the support plate for compressing the breast against the support plate, and a controller configured to control movement of the compression plate toward and away from the support plate. The controller is configured to adjust at least one of a rate of compression and a pressure applied to the breast based on a measurement of at least one of a diastolic pressure and a systolic pressure of the patient taken during at least one of a compression phase and a clamping phase of the mammography apparatus.

Apparatus and method for mammographic breast compression

An imaging system and related method are provided. The imaging system comprises a surface configured to support a portion of a patient's body, compression paddle configured to compress the portion of a patient's body against the surface, the compression paddle movable between an upper position and a lower position; and a compression control in direct or indirect communication with the compression paddle and configured to effectuate displacement of the compression paddle to any position between and including the upper position and the lower position upon receiving a patient input or command. The system may further comprise a feedback device configured to provide, to the patient, information indicative of the quality of the image that would be achieved at a corresponding compression paddle position to assist the patient in selecting a desirable compression paddle position.

Breast imaging system giving feedback information to the patient and method using thereof

A method of obtaining x-ray images includes controlling operation of an automatic injector to inject a contrast agent into a patient at a predetermined time, synchronizing operations of an x-ray imaging system with the operation of the automatic injector, and obtaining images of a region of interest of the patient during arterial and diffusion phases of the contrast agent.

Method and apparatus for contrast-enhanced spectral mammography programmed sequences

Apparatus, systems, and methods for computer-aided detection are disclosed and described. An example apparatus includes at least one processor and a memory. The example memory includes instructions which, when executed, cause the at least one processor to at least: associate first patient data and first outcome data according to a set of association rules; train a processing model using machine learning and the associated first patient data and first outcome data; generate a computer-aided decision processing algorithm using the processing model; update the computer-aided decision processing algorithm based on at least one of second patient data or second outcome data received from a cloud infrastructure; and deploy the updated computer-aided decision processing algorithm to be applied to third patient data.

Methods and apparatus for self-learning clinical decision support

A method of contrast enhanced breast imaging, comprising injecting a contrast agent in a breast of a patient, imaging at the same time both said breast and a reference insert containing at least one known concentration of said contrast agent, quantifying enhancement of contrast enhanced breast image by comparing said breast image and reference insert image.

Method of contrast enhanced breast imaging, and contrast agent reference insert

Growing community of inventors

Paris, France

Razvan Iordache