Abstract: A resource management system for better operation of a plurality of devices. The system comprises an input interface (IN) for receiving input data including one or more characteristics of at least one work object (P1-P3) and/or including context data. The at least one work object (P1-P3) can be processed by one or more processing devices (Mij). The said processing is specified in a respective work specification (S1-S3). A predictor component (PC) of the system is configured to predict, based on the input data, a change to the work specification. The system comprises an output interface (OUT) for providing output data that represents said predicted change.

Abstract: In a method of segmenting a feature in an image, an image product related to the image is provided (102) to a model trained using a machine learning process. An indication of a shape descriptor for the feature in the image is received (104) from the model, based on the image product. The indicated shape descriptor is then used (106) in a model based segmentation, MBS, to initialize the MBS and segment the feature.

Abstract: The invention relates to a system for assisting in evaluating a contour of an anatomic structure (22) with respect to a dose distribution corresponding to a treatment plan for a radiation therapy treatment of a patient. The system comprises an evaluation unit particularly configured to evaluate the dose distribution in varying distances from the contour of the anatomic structure (22) to determine at least one point where the evaluated dose distribution fulfills a predetermined condition, and to determine the distance between the at least one point and the contour and/or to visualize the at least one point to a user of the system.

Abstract: The present disclosure relates to a method for controlling a magnetic resonance imaging guided radiation therapy apparatus comprising a magnetic resonance imaging system.

Abstract: The invention relates to a medical image data processing system (101) for image segmentation. The medical image data processing system (101) comprises a machine learning framework trained to receive an anatomical position of a voxel and to provide a tissue type classification. An execution of machine executable instructions by a processor (130) of the medical image data processing system (101) causes the processor (130) to control the medical image data processing system (101) to: —receive medical image data (140) comprising an anatomical structure of interest, —fit an anatomical frame of reference (302, 402) to the medical image data (140) using model-based segmentation, —classify tissue types represented by voxels of the medical image data (140) using the machine learning framework, wherein anatomical positions of the voxels with respect to the anatomical frame of reference (302, 402) are used as the input to the machine learning framework.

Abstract: The invention provides for a medical apparatus (100, 400, 600) comprising a memory (110) for storing machine executable instructions (120) and a processor (104) for controlling the medical apparatus. Execution of the machine executable instructions causes the processor to: receive (200) a medical image (122) descriptive of a three-dimensional anatomy of a subject (418); and provide (202) an image segmentation (124) by segmenting the medical image into multiple tissue regions (300, 302) using a model-based segmentation. The model-based segmentation assigns a tissue type to each of the multiple regions. The model-based segmentation has a surface mesh (304). The segmentation is corrected by using the tissue type assigned to each of the multiple regions to correct for partial volume effects at boundaries formed by the surface mesh between at least some of the multiple tissue regions.

Abstract: The invention relates to a system for assisting in evaluating a contour of an anatomic structure (22) with respect to a dose distribution corresponding to a treatment plan for a radiation therapy treatment of a patient. The system comprises an evaluation unit particularly configured to evaluate the dose distribution in varying distances from the contour of the anatomic structure (22) to determine at least one point where the evaluated dose distribution fulfills a predetermined condition, and to determine the distance between the at least one point and the contour and/or to visualize the at least one point to a user of the system.

Abstract: The invention relates to a medical image data processing system (101) for image segmentation. The medical image data processing system (101) comprises a machine learning framework trained to receive an anatomical position of a voxel and to provide a tissue type classification. An execution of machine executable instructions by a processor (130) of the medical image data processing system (101) causes the processor (130) to control the medical image data processing system (101) to: —receive medical image data (140) comprising an anatomical structure of interest, —fit an anatomical frame of reference (302, 402) to the medical image data (140) using model-based segmentation, —classify tissue types represented by voxels of the medical image data (140) using the machine learning framework, wherein anatomical positions of the voxels with respect to the anatomical frame of reference (302, 402) are used as the input to the machine learning framework.

Abstract: The invention relates to the planning of a radiation therapy treatment of at least one structure in a region of a patient body. A planning unit obtains a first treatment plan generated on the basis of a planning image of the body region and on the basis of dose objectives. Moreover, the planning unit receives a further image of the body region of the patient body, determines a transformation for generating an adapted treatment plan from the first treatment plan and/or for generating an adapted dose distribution from the dose distribution corresponding to the first treatment plan on the basis of the further image and determines an adapted treatment plan on the basis of the transformation and/or the adapted dose distribution. In accordance with the invention, the transformation on the basis of the dose objectives.

Abstract: The present invention relates to an apparatus for adaptive contouring of a body part. It is described to provide (210) at least one image; wherein, the at least one image comprises a first image comprising image data of a body part. An initial automatic model based segmentation of image data of the body part in the first image is determined (220). Final segmentation data of the body part is determined (230) in response to a modification of the initial automatic model based segmentation. An updated model based segmentation can be applied (240) on the basis of the initial automatic model based segmentation and the final segmentation data.

Abstract: The present invention teaches a method and system for computing an alternative electron density map of an examination volume. The processing system is configured to compute a first electron density map using a plurality of imaging data, compute a second electron density map, wherein the second electron density map is a simplified version of the first electron density map, and compute the alternative electron density map, using the first electron density map and the second electron density map.

Abstract: The invention relates to a medical image data processing system (101) for image segmentation. The medical image data processing system (101) comprises a processor (130) for controlling the medical image data processing system (101), wherein execution of the machine executable instructions by the processor (130) causes the processor (130) to control the image data processing system (101) to: —receive medical image data (140), —generate a segmentation of an anatomical structure of interest comprised by the medical image data (140), —convert the segmentation to a surface mesh representation of the anatomical structure of interest, —compare the surface mesh representation with the reference surface mesh representation of the anatomical reference structure using spectral matching, wherein one or more spectral embeddings of the two meshes are matched, —providing an area of topological mismatch of C the surface mesh representation with the reference surface mesh representation.

Abstract: The invention relates to a system and a method for evaluating a treatment plan for an external radiation therapy treatment, the treatment plan comprising parameters for controlling an external radiation therapy apparatus during the treatment. The system comprises a database storing historic treatment plans and storing for each historic treatment plan a quality parameter indicative of whether a deviation between a planned dose distribution and a measured dose distribution resulting from an execution of the treatment plan is within an acceptable limit. An evaluation unit determines a threshold value for each of a plurality of treatment plan metrics based on the historic treatment plans and the associated quality parameters. Further, the evaluation unit calculates a value of each of the metrics for the treatment plan and compares the value of each of the metrics with the threshold value determined for the respective metric.

Abstract: A resource management system for better operation of a plurality of devices. The system comprises an input interface (IN) for receiving input data including one or more characteristics of at least one work object (P1-P3) and/or including context data. The at least one work object (P1-P3) can be processed by one or more processing devices (Mij). The said processing is specified in a respective work specification (S1-S3). A predictor component (PC) of the system is configured to predict, based on the input data, a change to the work specification. The system comprises an output interface (OUT) for providing output data that represents said predicted change.

Abstract: A medical apparatus (300, 400, 500) includes a magnetic resonance imaging system (302) for acquiring magnetic resonance data (342) from an imaging zone (308); a processor (330) for controlling the medical apparatus; a memory (336) storing machine executable instructions (350, 352, 354, 356). Execution of the instructions causes the processor to: acquire (100, 200) the magnetic resonance data using a pulse sequence (340) which specifies an echo time greater than 400 ?s; reconstruct (102, 202) a magnetic resonance image using the magnetic resonance data; generate (104, 204) a thresholded image (346) by thresholding the magnetic resonance image to emphasize bone structures and suppressing tissue structures in the magnetic resonance image; and generate (106, 206) a bone-enhanced image by applying a background removal algorithm to the thresholded image.

Abstract: An imaging method for identifying abnormal tissue in the lung is provided, comprising the recording of slice images of the lung by means of X-ray radiation, recording of blood vessels, differentiation of blood vessels and abnormal tissue, segmentation of the abnormal tissue and display of the segmented abnormal tissue on an output device. In addition, a computer tomograph for identifying abnormal tissue in the lung is provided, having a radiation source for recording slice images of the lung and blood vessels by means of X-ray radiation, a computer unit for differentiating the blood vessels from the abnormal tissue and for segmenting the abnormal tissue, as well as an output device for displaying the segmented abnormal tissue.

Abstract: The present invention relates to an apparatus for adaptive contouring of a body part. It is described to provide (210) at least one image; wherein, the at least one image comprises a first image comprising image data of a body part. An initial automatic model based segmentation of image data of the body part in the first image is determined (220). Final segmentation data of the body part is determined (230) in response to a modification of the initial automatic model based segmentation. An updated model based segmentation can be applied (240) on the basis of the initial automatic model based segmentation and the final segmentation data.

Abstract: An oncology monitoring system comprises: an image analysis module (42, 44) configured to perform an oncological monitoring operation based on images of a subject, for example acquired by positron emission tomography (PET) and computed tomography (CT); and a clinical guideline support module (10). The clinical guideline support module is configured to: display a graphical flow diagram (GFD) of a clinical therapy protocol for treating the subject comprising graphical blocks (B0, B1, B2, B3, B4, B5, B21, B211, B22, B221, B222, B223, B23, B231, B232) representing therapeutic or monitoring operations of the clinical therapy protocol including at least one monitoring operation performed by the image analysis module; annotate a graphical block of the graphical flow diagram with subject-specific information pertaining to a therapeutic or monitoring operation represented by the graphical block; and display an annotation (POP) of a graphical block (B211) responsive to selection of the graphical block by a user.

Abstract: The invention relates to a system and a method for evaluating a treatment plan for an external radiation therapy treatment, the treatment plan comprising parameters for controlling an external radiation therapy apparatus during the treatment. The system comprises a database storing historic treatment plans and storing for each historic treatment plan a quality parameter indicative of whether a deviation between a planned dose distribution and a measured dose distribution resulting from an execution of the treatment plan is within an acceptable limit. An evaluation unit determines a threshold value for each of a plurality of treatment plan metrics based on the historic treatment plans and the associated quality parameters. Further, the evaluation unit calculates a value of each of the metrics for the treatment plan and compares the value of each of the metrics with the threshold value determined for the respective metric.

Abstract: A device, system and method for generating one or more simulated CT images from MR images, including retrieving MR image data for one or more body parts of a living being, said MR image data including a plurality of pixels and/or voxels, analyzing said MR image data to identify one or more tissue and/or material types for one or more of said plurality of pixels and/or voxels, registering one or more reference data sets to said identified one or more tissue and/or material types, said reference data sets corresponding to a specific one of said identified tissue and/or material types, said reference data sets including reference values, and computing one or more simulated CT images by assigning said reference values to said pixels and/or voxels corresponding to said identified one or more tissue and/or material types.