Koninklijke Philips Corporation N.v.

Rolf Juergen Weese

Harald Sepp Heese

Alfonso Agatino Isola

Torbjoern Vik

Jens Wiegert

Christoph Neukirchen

Tom Brosch

Maria Luiza Bondar

Nick Flaeschner

Jochen Peters

Charles Loeb Truwit

Guenter Zeitler

Tobias Wissel

Matthias Lenga

Kay Sun

Dominique Siu Li Tio

Cheryl Kimberley Sital

Some embodiments are directed to a segmentation of medical images. For example, a medical image may be registering to multiple atlas images after which a segmentation function may be applied. Multiple segmentation may be fused into a final overall segmentation. The atlas images may be selected on the basis of high segmentation quality or low registration quality.

Medical image segmentation and atlas image selection

In a method of segmenting a tubular feature in an image, a sequence of overlapping portions of the image are segmented using a trained model. The overlapping portions are positioned along the length of the tubular feature and combined to determine a segmentation of the tubular feature.

Segmentating a tubular feature

Disclosed herein is a medical system () comprising a memory () storing machine executable instructions (). The medical system further comprises an anatomical detection module (). The anatomical detection module is configured for detecting an anatomical deviation in response to inputting tomographic medical scout image data (). The anatomical detection module is configured for outputting a localization () of the anatomical deviation in the tomographic medical scout image data if the anatomical deviation is detected. The medical system further comprises a processor () configured for controlling the medical system. Execution of the machine executable instructions causes the processor to: receive () the tomographic medical scout image data, receive () the localization of the anatomical deviation from the anatomical detection module in response to inputting the tomographic medical scout image data into the anatomical detection module, and provide () a warning signal () if the localization is received.

Automated scout scan examination

The invention relates a system for assisting in planning a radiation therapy treatment provided using a treatment plan comprising irradiation parameters for controlling a delivery of radiation. The system is configured to (i) receive a first dose distribution, (ii) obtain a first objective function, which depends upon at least one parameter and a dose distribution, (iii) determine a first value of the parameter such that the first objective function fulfills a predefined criterion when being evaluated for the first value of the parameter and for a second dose distribution derived from the first dose distribution, (iii) provide the first objective function in connection with the first value of the at least one parameter to a user for modifying the first objective function to generate a second objective function, and (v) determine the treatment plan using the second objective function. Further, the invention relates to a corresponding method and computer program.

Radiation therapy planning

The invention relates to a planning apparatus for planning a radiation therapy. A medical image, in which a target to be irradiated is indicated, is reformatted based on ray geometries to be used during the radiation therapy to be planned, resulting in several reformatted medical images. Radiation therapy parameters being indicative of intensities of raysto be used for irradiating a targetare determined based on the reformatted medical images by using a neural network unit. This allows to determine high quality radiation therapy parameters and hence allows for an improved planning of a radiation therapy. In particular, radiation and absorptions physics can be captured better, which can lead to the improved quality.

Planning apparatus for planning a radiation therapy

A system includes a computing system with a processor and computer readable storage medium with computer readable and executable instructions, including a radiation plan module, a radiation plan optimization module and a radiation plan visualization module. The processor is configured to execute the instructions, which causes the processor to construct and visually present, via a display monitor, a two-dimensional plot with three-dimensions of data from a radiation plan, and two dimensions along two axes of the plot and a third dimension represented through intensity.

Visualization of volumetric modulated arc therapy (VMAT) plans

The invention relates to a segmentation system for segmenting an object in an image. The segmentation system is configured to place a surface model comprising surface elements within the image, to determine for each surface element a respective sub volume () of the image and to use a neural network () for determining respective distances between the surface elements and the boundary of the object in the image based on the determined subvolumes. The surface model is then adapted in accordance with the determined distances, in order to segment the object. This segmentation, which is based on the subvolumes of the image and the neural network, is improved in comparison to known techniques which rely, () for instance, on a sampling of candidate points along lines being perpendicular to the respective surface element and on a determination of likelihoods for the candidate points that they indicate a boundary of the object.

Segmentation system for segmenting an object in an image

The invention relates to a dynamic sliding-window-like initialization for, for example, iterative VMAT algorithms. Specifically, a dynamic sliding window conversion method is contemplated where typical dynamic VMAT constraints are taken into account to find an optimal set of suitable openings (i.e. binary masks) that can be used as quasi-feasible start initialization for any VMAT algorithm that can refine until a deliverable plan is reached. Here, a multileaf leaf tip trajectory least square constrained optimization is performed to find a set of optimal unidirectional trajectories for all MLC leaf pairs of all arc points. To ensure that a quasi-feasible (or better quasi-deliverable) solution is returned, for example, a maximum dose rate, a maximum gantry speed, a maximum leafs speed, and a maximum treatment time may be enforced.

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Norderstedt, Germany

Rolf Juergen Weese