Ge Precision Healthcare LLC

General Electric Company

Buer Qi

Dejun Wang

Gireesha Chinthamani Rao

Yaan Ge

Gopal Biligeri Avinash

Sylvain Bernard

Tao Tan

Huanzhong Li

Wei Zhao

Yan Sun

Vincent Jonas Bismuth

Katelyn Rose Nye

Lehel Ferenczi

German Guillermo Vera Gonzalez

Jingyi Yang

Qingming Peng

Aizhen Zhou

Najib Akram

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

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

Systems/techniques that facilitate AI-based region-of-interest masks for improved data reconstructions are provided. In various embodiments, a system can access a set of two-dimensional medical scan projections. In various aspects, the system can generate a set of two-dimensional region-of-interest masks respectively corresponding to the set of two-dimensional medical scan projections. In various instances, the system can generate a region-of-interest visualization based on the set of two-dimensional region-of-interest masks and the set of two-dimensional medical scan projections. In various cases, the system can generate the set of two-dimensional region-of-interest masks by executing a machine learning segmentation model on the set of two-dimensional medical scan projections.

AI-based region-of-interest masks for improved data reconstruction

A training method () and system for a collimator border detection method. The training method () comprises the following steps: obtaining an original image acquired by an X-ray imaging system and a processed image obtained after processing the original image (); determining on the basis of the processed image whether the processed image is a valid image (); and extracting coordinates of a collimator border of a valid processed image, putting into a training pool the extracted coordinates of the collimator border and the original image corresponding to the valid processed image, and when the number of valid original images in the training pool reaches a preset threshold value, starting the training of the collimator border detection method ().

Training method and system for collimator border detection method

Various methods and systems are provided for x-ray imaging. In one embodiment, a method for an image pasting examination comprises acquiring, via an optical camera and/or depth camera, image data of a subject, controlling an x-ray source and an x-ray detector according to the image data to acquire a plurality of x-ray images of the subject, and stitching the plurality of x-ray images into a single x-ray image. In this way, optimal exposure techniques may be used for individual acquisitions in an image pasting examination such that the optimal dose is utilized, stitching quality is improved, and registration failures are avoided.

Method and systems for anatomy/view classification in x-ray imaging

The present application provides a medical imaging method and system and a non-transitory computer-readable storage medium. The medical imaging method comprises obtaining an original image acquired by an X-ray imaging system, and post-processing the original image based on a trained network to obtain an optimized image after processing.

Medical imaging method and system

Growing community of inventors

Beijing, China

Buer Qi