Koninklijke Philips Corporation N.v.

Eran Rubens

Yuechen Qian

Eliahu Zino

Bella Fadida-Specktor

Menachem Melamed

Eran Meir

Netanel Weinberg

Brian David Gross

Merlijn Sevenster

Shlomo Gotman

John Blair

Yugang Jia

Ayman Alalao

Thomas Andre Forsberg

Qianxi Li

Maria Kaplinsky Nus

Maria Kaplinsky

A system and/or method that facilitates sharing image viewing context between vendor visualization applications without integration of different software application from different vendors packages is describe herein. In one instance, a visualization computing system () includes a processor () that executes computer readable instructions that capture a visual context of an imaging study displayed via a basic visualization application running on a vendor computing system, identify the study based on the captured visual context, load the study on the visualization computing system, and launch an advanced visualization application, which allows viewing and manipulation of the loaded study using advanced visualization tools unavailable by the basic visualization application.

Image visualization of medical imaging studies between separate and distinct computing system using a template

A patient monitor () includes a display (). Patient values () are obtained for one or more known variables of a risk prediction function (). One or more unknown variables of the risk prediction function are determined, and at least one hyperplane () is defined as values assumable by the one or more unknown variables. Values of the risk prediction function are computed over the at least one hyperplane using the obtained patient values. A visualization template is selected from a database of visualization templates () using template selection indices including the risk prediction function and the one or more unknown variables. Using the visualization template, a visualization () of the computed values of the risk prediction function over the at least one hyperplane is displayed.

Contextualized patient-specific presentation of prediction score information

A computer-implemented method () reduces processing time of an application for visualizing image data, which application is one of a plurality of applications selectable by a user. Each of the plurality of applications includes a pre-processing algorithm for pre-processing the image data. The method predicts which one of the pre-processing algorithms is to be performed in response to a selection of an application by the user by: &#x2014;extracting a feature vector from the image data, metadata, and/or additional data associated with the image data, &#x2014;supplying the feature vector as input to a machine learned model, and &#x2014;receiving an algorithm identifier as output from the machine learned model. The algorithm identifier identifies the pre-processing algorithm. Additionally, the algorithm identifier is used to select () the pre-processing algorithm. The image data is pre-processed () using the selected pre-processing algorithm.

Image data pre-processing

A computer-implemented method () of reducing processing time of an application for visualizing image data, the application being one of a plurality of applications selectable by a user and each of the plurality of applications comprising a pre-processing algorithm for pre-processing the image data. The method comprises predicting which one of the pre-processing algorithms is to be performed in response to a selection of an application by the user by:

A system () for enabling study of image data, comprising: &#x2014;a user interface subsystem () for i) receiving navigation commands () from a user, and ii) displaying different views () of the image data () in response to the navigation commands for enabling the user to navigate through the image data; &#x2014;a function execution subsystem () for executing individual ones of a plurality of system functions () to support the user in the study of the image data; and&#x2014;a pattern analysis subsystem () for: j) obtaining, from the user interface subsystem, data () indicative of a display sequence of the different views during the navigating through the image data, jj) analyzing the data to determine a navigation pattern () of the user, and jjj) based on the navigation pattern, selecting one of the plurality of system functions for execution by the function execution subsystem.

Enabling a user to study image data

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Haifa, Israel

Eran Rubens