General Electric Company

Ge Precision Healthcare LLC

General Electric Corporation Gmbh

La Science Sas

Vincent Jonas Bismuth

Regis Vaillant

Sylvain Bernard

Jean Lienard

Régis Vaillant

Jorge Corsino Espino

Sebastien Gorges

Gopal Biligeri Avinash

Lionel Francois Desponds

Fanny Patoureaux

Vincent Auvray

Yves Lucien Trousset

Gireesha Chinthamani Rao

Tao Tan

Pál Tegzes

Dejun Wang

Pablo Milioni De Carvalho

Buer Qi

Barbara Grosjean Leh

Martin Deterre

Romain Moulin

Cyril Riddell

Yaan Ge

Erwan Kerrien

German Guillermo Vera Gonzalez

Jeremie Pescatore

Maxime Cazalas

Renaud Heitz

Liliane Ramus

Sébastien Gorges

Marie-Odile Berger

Yana Popova

Xavier Mancardi

Laurence Gavit-Houdant

Benjamin Didier Réne Wimille

Karima Santi

Qingming Peng

Michel S Tohme

Tamás Ujvári

Zsolt Szabó

Sebastian Gorges

Daniel Gannat

Shri R Rajesh Prabhu

Bruno Vigan

Sekar Anantharaman

Maria Belen Aguirre Larrieu

Olivier Ernoult

Ludovic Boilevin Kayl

Fabio Mattana

Romain Brevet

Mathilde Ravier

Gabor Simon

Guillaume Buc

Xavier Beuque

Tamas Ujvari

Zsolt Szabo

Gyorgy Szekely

Székely György

Various methods and systems are provided for enhancing the generation of a synthetic 2D image from tomosynthesis projection images, such as a synthetic 2D image. To enhance the image, the image processing system utilizes a selected height interval to scan for objects of interest within a volume reconstructed from the tomosynthesis projection images. The height interval is larger than normal slices formed from the reconstructed volume, such that pixel information on larger masses can be obtained from adjacent slices within the volume. Further, the illustration of the object of interest in the synthetic 2D image can be modified by contributing pixel information from all tomosynthesis projections for the presentation of the object or interest. The use of pixel information from all tomosynthesis projections enhances the illustration of the high frequency components and the low frequency components of the object of interest within the enhanced image.

System and method for projection enhancement for synthetic 2D image generation

The present invention pertains to a system for projecting a pattern of interest onto a retinal area of a human eye, containing a carrying frame for being worn by a patient, a camera for capturing an image, a projector device for projecting a pulsed light beam reflecting a pattern of interest into a human eye, and a processor device being in communication with the camera and the projector device, wherein the processor device is adapted for converting the image captured by the camera into the pattern of interest being basis for the pulsed light beam, wherein the projector device and the camera are attached to the carrying frame.

System for projecting a pattern of interest onto a retinal area of a human eye

Various methods and systems are provided for denoising images. In one example, a method includes obtaining an input image and a noise map representing noise in the input image, generating, from the noise map and based on a calibration factor, a strength map, entering the input image and the strength map as input to a denoising model trained to output a denoised image based on the input image and the strength map, and displaying and/or saving the denoised image output by the denoising model.

Methods and systems for image denoising

Various systems are provided for non-uniform thickness and/or sampling of slabs of the breast to present DBT acquisitions. A method for generating a patient image as a set of slabs representing an imaged object, the method comprising acquiring a tomosynthesis projection, reconstructing a series of slab images, each slab representing a portion of a breast, and a plurality of slabs of non-uniform thickness and/or non-uniform sampling in a 3D reconstructed domain defined by x-, y-, and z-axes.

Methods and systems for breast tomosynthesis

A convolutional neural network (CNN) is employed in an automated feature and/or anomaly detection system for analyzing images provided by X-ray imaging system. The automated detection system operates in a manner that reduces the number of full-resolution CNN convolution layers required in order to speed up the network inference and learning processes for the detection system. To do so, the detection system utilizes as an input a more compact representation of the tomographic data to alleviate the CNN memory footprint and computation time issues in prior art X-ray systems.

Fast and low memory usage convolutional neural network for tomosynthesis data processing and feature detection

A tomosynthesis machine allows for faster image acquisition and improved signal-to-noise by acquiring a projection attenuation data and using machine learning to identify a subset of the projection attenuation data for the production of thinner slices and/or higher resolution slices using machine learning.

X-ray tomosynthesis system providing neural-net guided resolution enhancement and thinner slice generation

Various methods and systems are provided for x-ray imaging. In one embodiment, a method includes acquiring, with an x-ray detector, an x-ray image of a subject, determining a transformation that minimizes anti-scatter grid artifacts in the x-ray image, correcting the x-ray image according to the transformation to generate a corrected image, and outputting the corrected image. In this way, artifacts arising from a misalignment of an anti-scatter grid between the calibration and the acquisition may be reduced.

Method and systems for removing anti-scatter grid artifacts in x-ray imaging

This disclosure proposes to speed up computation time of a convolutional neural network (CNN) by leveraging information specific to a pre-defined region, such as a breast in mammography and tomosynthesis data. In an exemplary embodiment, a method for an image processing system is provided, comprising, generating an output of a trained convolutional neural network (CNN) of the image processing system based on an input image, including a pre-defined region of the input image as an additional input into at least one of a convolutional layer and a fully connected layer of the CNN to limit computations to input image data inside the pre-defined region; and storing the output and/or displaying the output on a display device.

Systems and methods for fast mammography data handling

Various methods and systems are provided for mammogram imaging. In one example, a method for an x-ray mammography system includes determining, based on a pre-exposure image of a subject acquired with the x-ray mammography system before acquisition of one or more main images, that the subject has an implant; automatically adjusting one or more imaging parameters in response to determining that the subject has the implant; and acquiring the one or more main images with the adjusted one or more imaging parameters.

Methods and systems for automatic implant detection in mammography

Various methods and systems are provided for reducing blur in a diagnostic image. In one example, a method includes reducing blur in a diagnostic image by applying a deconvolution filter to the diagnostic image, the deconvolution filter generated from a point spread function (PSF) estimation of blur at each pixel of the diagnostic image, the PSF estimation generated based on a motion vector field between the diagnostic image and a pre-shot image acquired prior to the diagnostic image.

Methods and systems for digital mammography imaging

Various methods and systems are provided for tracking a biopsy target across one or more images. In one example, a method includes determining a position of a biopsy target in a selected image of a patient based on an image registration process with a reference image of the patient, and displaying a graphical representation of the position of the biopsy target on the selected image.

An image processing method applied by a medical imaging device is proposed, including at least one camera and at least one display screen on which is displayed a medical image showing a region of interest of a patient, the method being characterized in that the region of interest is determined by the following steps, the screen and the camera being laid out so as to be facing a practitioner simultaneously, acquisition by the camera of at least one tracking image containing the eyes of the practitioner, analysis of the tracking image so as to localize in the medical image at least one pixel of interest contemplated by the practitioner on the screen from the orientation of the eyes of the practitioner, processing the medical image so as to select the region of interest from the localized pixel of interest.

Method for medical image processing

A method for tracking the position of a person in an environment, such as a medical room, relative to a medical device is presented. The method comprises identifying the position of a medical device in the environment, providing a mobile device in the vicinity of a person in the environment, the mobile device configured to follow movement of the person in the environment, and identifying the position of the mobile device in the environment by using at least one stationary device. Further, the method comprises using a processor to process data relating to the position of the mobile device in the environment to obtain an expected position of the person in the environment, data relating to the position of the medical device in the environment, and data relating the expected position of the person in the environment to obtain an expected relative position of the person with respect to the medical device.

Method and system for tracking a person in a medical room

This disclosure relates to a three dimensional visualization method for visualizing and/or displaying a limited zone of a patient's vasculature, the method comprising selecting an entry point within an imaged vasculature and three dimensionally visualizing a simulated contrast agent propagation from the selected entry point in a limited zone of the imaged vasculature.

Three dimensional imaging method of a limited zone of a patient's vasculature

A method is provided for monitoring the radiation dose in a body to be imaged using an X-ray imaging device comprising an X-ray emitting source, a detector, a processing unit and a display. The method comprises exposing the body to be imaged to radiation doses to acquire initial 2D images; computing a 3D model of the body in relation to the initial 2D images using the processing unit; applying a model of the interactions between matter and radiation to the 3D model of the body using the processing unit; calculating, using the processing unit, a dose map of the distribution of the accumulated radiation dose in the 3D model for parameters that define the conditions of X-ray exposure; and displaying the 3D model of the body oriented according to the position of the emitting source with the dose map.

Selection of optimal viewing angle to optimize anatomy visibility and patient skin dose

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Paris, France

Vincent Jonas Bismuth