Siemens Medical Solutions Usa, Inc.

Siemens Healthcare Gmbh

Canon Medical Systems Corporation

Siemens Aktiengesellschaft

John Baumgart

Joseph Manak

James Begelman

John Christopher Rauch

George F Kramp

Gary S Martucci

Martin Trini

Benita Devadas

Yi Hu

Kevin Christopher Zimmerman

Thomas Labno

Yu-Bing Chang

Florian Vogt

Guang Yang

Christian Kaethner

Christopher Rohkohl

Akira Nishijima

Weng Lei

Sebastian Schafer

Soroosh Kargar

Haruki Iwai

Thomas A Ruggiero

Victor Gorin

Olivier Ecabert

Michael J Keller

Priyendu Subashchandran

Takashi Ohshima

Abdul Salim Vahabudeen

Abhishek Bafna

Christopher Drexler

Gerhard Litz

Weifeng Shang

Rui Hua

A system and method is provided for controlling an acquisition system to obtain, based on a currently acquired set of projection data, a next set of projection data that is to be acquired using a set of learned imaging conditions. The set of learned imaging conditions are, at least in part, based on training data including projection data and dose information. In one embodiment, the initial dose and angle for obtaining the initial set of projection data are chosen at random. In another embodiment, the initial dose and angle for obtaining the initial set of projection data are chosen based on a test scan and a trained neural network for outputting the initial dose and angle using a loss function.

Apparatus, method, and non-transitory computer-readable storage medium for generating a task-aware dynamic sparse-view scanning procedure

A computer-tomography (CT) imaging system, comprising an imaging data acquisition system. The imaging data acquisition system includes a detector section, an aggregation section, and a storage section. The detection section includes a plurality of detector elements configured to convert radiation into electric signals. The aggregation section aggregates imaging data carried by the electric signals from the detector section. The storage section is arranged in a manner corresponding to the detector elements regarding an output from the detector section and an input to the aggregation section. The storage section includes a predetermined number of non-volatile memories configured to store the imaging data from the corresponding detector elements.

Computed tomography (CT) imaging system, radiation imaging system, and method of acquiring CT imaging data

A method includes obtaining, at a local imaging system, projection data for an object representing an intensity of radiation detected along a plurality of rays through the object using a first set of imaging parameters; transmitting an image quality dataset related to the obtained projection data to a remote server; generating, via the remote server, localized restoration information based on the received image quality dataset; transferring the localized restoration information from the remote server to the local imaging system; and updating the local imaging system using the localized restoration information.

Method and system for automatic deployment of image restoration parameters

A general workflow for deep learning based image restoration in X-ray and fluoroscopy/fluorography is disclosed. Higher quality images and lower quality images are generated as training data. This training data can further be categorized by anatomical structure. This training data can be used to train a learned model, such as a neural network or deep-learning neural network. Once trained, the learned model can be used for real-time inferencing. The inferencing can be more further improved by employing a variety of techniques, including pruning the learned model, reducing the precision of the learned mode, utilizing multiple image restoration processors, or dividing a full size image into snippets.

X-ray imaging restoration using deep learning algorithms

A control method for controlling data processing acquired from medical imaging modalities by using multiple data processors connected to multiple medical imaging modalities via a network. The method includes obtaining image information for imaging to be performed with an imaging modality from the multiple imaging modalities. The method also includes obtaining load information of the multiple data processors before the imaging is completed. Allocating, based on graph information generated based on the obtained load information, at least a part of the multiple data processors to processing of data acquired in imaging based on the imaging information. The control method may conclude by performing processing of the acquired data with the allocated data processing resource.

Task allocation for use in medical imaging and diagnostics

A computer-tomography (CT) imaging system, comprising an imaging data acquisition system. The imaging data acquisition system includes a plurality of sets of a detector section, a storage section, and an aggregation section. The detector section includes a plurality of detector elements each being configured to convert radiation into electric signals. The aggregation section is configured to aggregate imaging data carried by the electronic signals from the detector section. The storage section is connected with an output of the detector section and an input of the aggregation section. The storage section comprises a predetermined number of non-volatile memories to store the imaging data from the corresponding detector elements.

Imaging system and data acquisition method and structure thereof

A system and a method by which multiple regions or objects of interest can be indicated within an X-ray image, from which a user can select a primary region or object of interest and accordingly adjust the appropriate X-ray dose for obtaining a better quality image of the selected regions or objects of interest.

System and method for indication and selection of region of interest for x-ray dose adjustment

A method of imaging includes obtaining a first image including projection data representing an intensity of X-rays detected by a plurality of detectors at a first X-ray exposure setting, the X-rays being emitted from an X-ray source; based on a detection result of a first object in the first image: determining a background region of interest (ROI) around the first object, the background ROI including background ROI pixels having a first intensity value corresponding to the intensity of the X-rays; and converting, for each pixel of the background ROI pixels, the first intensity values of the background ROI pixels to a normalized X-ray attenuation factor; and determining a second X-ray exposure setting for use in obtaining a second image based on the background ROI pixels converted to the normalized X-ray attenuation factor.

Method and apparatus for automatic determination of object and background region of interest for real-time automatic dose rate control in dynamic imaging systems

Systems and methods are provided for image forecasting of image processing. A trained image forecaster may be used to generate a virtual image based on prior actual images. The virtual image may be preprocessed to generate an intermediate image. The intermediate image may then be used to process the next actual image to generate a final image.

Forecasting images for image processing

A medical workflow system is provided that includes at least one database configured to store one or more programs that operate a patient imaging device, patient data corresponding to one or more patients, medical procedure data corresponding to a type of patient medical procedure, and user data identifying a user to conduct a medical procedure using the medical procedure data. The medical workflow system includes a workflow processor configured to determine which of the one or more programs to provide to the user based on at least one of the patient data, the medical procedure data and the user data. The medical workflow system also includes at least one user interface configured to provide a plurality of user selectable options comprising the determined one or more or programs. The workflow processor is further configured to execute a selected program that is selected from the one or more provided programs.

Medical scanner optimized workflow system

A system and method include reception of 3D imaging data showing blood flow over time in a patient volume including vessels, reception of a user input of a projection angle, generation of a plurality of 3D images based on the 3D imaging data, generation of a 2D digitally reconstructed radiograph (DRR) at the projection angle input by the user for one of the plurality of 3D X-ray images, and display of the 2D DRR image. Numerous other aspects are provided.

System and method for generating a time-encoded blood flow image from an arbitrary projection

A system and method includes reception of a plurality of fill frames of a patient volume, each of the plurality of fill frames depicting a contrast medium within the patient volume at a respective time, identification, for each pixel location of the fill frames, of a fill frame whose pixel at the pixel location is associated with a pixel value which represents a greater level of contrast medium than the pixel values of pixels at the pixel location within the others of the plurality of fill frames, generation of a peak contrast fill frame corresponding to each fill frame, the peak contrast fill frame corresponding to a given fill frame including, at pixel locations for which the given fill frame was identified, pixels associated with pixel values of the given fill frame, and storage of the plurality of peak contrast fill frames.

Contrast flow imaging system

A system and method includes reception of an indication of a region of interest of a plurality of image frames, determination of a first set of pixel locations of the region of interest which depict blood vessels, determination of a second set of pixel locations of the region of interest which depict non-vessel tissue, determination, for each of the plurality of the image frames, of a first contrast medium concentration corresponding to the first set of pixel locations, determination, for each of the plurality of the image frames, of a second contrast medium concentration corresponding to the second set of pixel locations, and display of a visualization depicting a first contrast medium concentration and a second medium concentration with respect to the respective time of each of the plurality of the image frames.

Determination and presentation of flow transit curves

A system and method includes reception of first two-dimensional projection images of a patient volume, each of the first two-dimensional projection images having been acquired from substantially a respective one of a plurality of projection angles during presence of at least a portion of contrast medium in arteries within the patient volume, reception of second two-dimensional projection images of the patient volume, each of the second two-dimensional projection images having been acquired from substantially a respective one of the plurality of projection angles during presence of at least a portion of the contrast medium in veins within the patient volume, generation, for each of the plurality of projection angles, of a composite two-dimensional image based on one of the first two-dimensional projection images acquired from substantially the projection angle and one of the second two-dimensional projection images acquired from substantially the projection angle, generation of a three-dimensional image based on the generated composite two-dimensional images, and display of an image based on the three-dimensional image.

System for acquiring a three-dimensional image of arteries and veins

Systems and methods are provided for angiographic roadmapping. In accordance with one aspect, the framework generates one or more two-dimensional (2D) digitally reconstructed radiograph (DRR) images from a four-dimensional (4D) digital subtraction angiography (DSA) image volume. A maximally opacified image is generated from at least one of the one or more 2D DRR images over a window of time. The maximally opacified image may then be integrated with a live fluoroscopic image and displayed for angiographic roadmapping.

Growing community of inventors

Hoffman Estates, IL, United States of America

John Baumgart