Ge Precision Healthcare LLC

General Electric Company

Samsung Electronics Co., Ltd.

Lenovo (Beijing) Limited

International Business Machines Corporation

Ge Medical Systems Global Technology Company, LLC

Beijing Lenovo Software Ltd.

Dejun Wang

Buer Qi

Yaan Ge

Huanzhong Li

Gireesha Chinthamani Rao

Jiali Zhao

Seokcheol Kee

Gopal Biligeri Avinash

Sylvain Bernard

Katelyn Rose Nye

Tao Tan

Aizhen Zhou

Bo Zhang

Tao Li

Wei Zhao

Yan Sun

Vincent Jonas Bismuth

Ravi Soni

Jin Wu

Haibing Ren

Jing Wu

Chunlei Zhao

German Guillermo Vera Gonzalez

Ming Yan

Venkata Ratnam Saripalli

Kun Tao

Dibyajyoti Pati

Xianfeng Ni

Nasir Ahmed Desai

Shaoping Peng

Junpyo Hong

Arun Kumar Chandrashekarappa

Yanling Qu

Tiantian Zhang

Qiu Xia Zhao

Jingyi Yang

Fuqiang Chen

Qingming Peng

Mei Lin

Srikrishnan V

Najib Akram

Yifei Song

Shunyong Yang

Shuai B J Tan

Jabri Kadri

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

Various methods and systems are provided for automatically registering and stitching images. In one example, a method includes entering a first image of a subject and a second image of the subject to a model trained to output a transformation matrix based on the first image and the second image, where the model is trained with a plurality of training data sets, each training data set including a pair of images, a mask indicating a region of interest (ROI), and associated ground truth, automatically stitching together the first image and the second image based on the transformation matrix to form a stitched image, and outputting the stitched image for display on a display device and/or storing the stitched image in memory.

Methods and systems for image registration

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

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

Method and systems for camera-aided x-ray imaging

An image processing method comprises: identifying a weak edge comprising a plurality of weak edge pixels and a strong edge comprising a plurality of strong edge pixels in an input image; filtering at least a part of said input image to obtain a smoothed image, during which said weak edge in said input image is filtered with a first filter and said strong edge in said input image is filtered with a second filter having a smoothness less than that of said first filter; acquiring edge information of said input image based on said input image and said smoothed image; and generating an output image based on said edge information and said smoothed image. The present invention further relates to an image processing system and an imaging system.

Image processing method, image processing system, and imaging system

This disclosure presents an image processing method and related X-ray imaging device The method comprises: calculating a relative displacement between two first images that are already in auto registration as a first displacement vector; calculating a difference between position information fed back by a position sensor on the X-ray imaging device when imaging exposure is performed on the two first images respectively as a second displacement vector; calculating a first error of the first displacement vector relative to the second displacement vector; calculating a registration level corresponding to the first error in accordance with a pre-stored training model which is a mathematical distribution model of second errors between a plurality of third displacement vectors and a plurality of corresponding fourth displacement vectors; and labeling the registration level on the two first images that are already in auto registration.

Image processing method and apparatus for X-ray imaging device

The present invention discloses a manager, a test agent installed on a personal mobile device and methods thereof. The manager comprises: a first network connection module configured to establish a connection with the mobile device through Internet, the mobile device being installed with a test agent for performing test operation on a mobile application on the mobile device; and a security module configured to communicate with the test agent through the first network connection module to make the test agent perform security control on the mobile device. According to the manager, mobile devices, and methods of the present invention, the cost such as maintenance cost of the data center and purchase cost of mobile devices can be reduced dramatically. It is not necessary to analyze market demands since mobile devices owned by the users of the mobile devices are the mobile devices that need to be tested by the tester.

Testing a mobile application

An electronic device and a direction switching method are described. The electronic device includes a housing having a first end and a second end, an audio input unit and an audio output unit. The electronic device has at least a first working direction and a second working direction, the direction from said first end to said second end is a reference direction when the electronic device is in the first working direction; and the direction from the second end to the first end is the reference direction when the electronic device is in the second working direction, wherein the audio input unit in a working state is located at the second end when the electronic device is in the first working direction; and the audio input unit in the working state is located at the first end when the electronic device is in the second working direction.

Electronic device and direction switching method of the electronic device

A display method and an electronic device are provided. The display method is applied to the electronic device, and includes: displaying each display object of the display unit according to a first display parameter, monitoring the operation state of the electronic device to obtain a monitored result; acquiring a display adjusting command if the monitored result indicates that a fold or unfold operation is performed on the electronic device; adjusting the first display parameter of at least one display object of the display unit according to the display adjusting command to generate a second display parameter, and displaying the at least one display object according to the second display parameter.

Display method and electronic device

A method for processing each of chest X-ray images photographed by an X-ray imaging apparatus, includes the steps of: analyzing characteristics of lung images in the chest X-ray images; sorting the chest X-ray images, based on said result of analysis; and displaying the result of sorting.

Method and apparatus for processing chest X-ray images

An apparatus for and method of performing a most informative feature extraction (MIFE) method in which a facial image is separated into sub-regions, and each sub-region makes individual contribution for performing facial recognition. Specifically, each sub-region is subjected to a sub-region based adaptive gamma (SadaGamma) correction or sub-region based histogram equalization (SHE) in order to account for different illuminations and expressions. A set of reference images is also divided into sub-regions and subjected to the SadaGamma correction or SHE. A comparison is made between the each corrected sub-region and each corresponding sub-region of the reference images. Based upon the comparisons made individually for the sub-regions of the facial image, one of the stored reference images having the greatest correspondence is chosen. While usable individually, using the MIFE and/or SadaGamma correction or SHE together achieves a lower error ratio in face recognition under different expressions, illuminations and occlusions.

Apparatus for and method of feature extraction for image recognition

A face detection method and apparatus using a level-set method. The method includes: laying a first initial shape model over a face image; evolving shape curves of the first initial shape model using the level-set method; detecting first through M-th neighboring boundary points that neighbor first through M-th initial boundary points of the first initial shape model, and that neighbor the evolved shape curves, M being a positive integer larger than 1; laying a modified shape model rendered using the detected first through M-th neighboring boundary points over the face image; detecting a rotation angle of the modified shape model; determining whether the detected rotation angle of the modified shape model is within a predetermined angle range; and selecting one of a second initial shape model, which is rotated to the left, or a third initial shape model, which is rotated to the right, according to the detected rotation angle, and laying the selected initial shape model over the face image, and returning to the detecting of the first through M-th neighboring boundary points, when the detected rotation angle of the modified shape model is outside the predetermined angle range.

Face detection method and apparatus using level-set method

Growing community of inventors

Beijing, China

Dejun Wang