Siemens Aktiengesellschaft

Siemens Healthcare Gmbh

Siemens Medical Solutions Usa, Inc.

Siemens Healthineers Ag

Anna Jerebko

Michael Kelm

Andreas Fieselmann

Rainer Graumann

Thomas Mertelmeier

Michael Suehling

Klaus Engel

Frank Dennerlein

Michael Wels

Olivier Pauly

Dorin Comaniciu

Shaohua Kevin Zhou

Sasa Grbic

Luca Bogoni

Shiras Abdurahman

Ralf Nanke

Thomas Schmitt

Tom Weidner

Daguang Xu

Michael Fuhrmann

Daniel Fischer

Siqi Liu

Sarang Lakare

Florin Cristian Ghesu

Eva Rumpel

Michael Sühling

Alexey Tsymbal

Clemens Joerger

Maria Jimena Costa

Julia Wicklein

Peter Bartl

Johan Nuyts

Christoph Luckner

Clemens Jörger

Stefan Veitenhansl

Koen Michielsen

Volker Biermann

Francois Nolte

A method for visualizing a region of interest inside an examination object into which an examination instrument has been introduced, and a tomosynthesis system for executing the method. Raw datasets are acquired from a number of lateral acquisition angles. A number of synthetic projections are calculated from the raw datasets. The synthetic projections are output in the form of an image sequence which represents the examination object in a rotating visualization. An image reconstruction device and a tomosynthesis system, as well as a computer program product and a computer-readable medium are described.

Method and image reconstruction device for visualizing a region of interest, tomosynthesis system and computer program product

A first x-ray image is acquired at a predetermined position of a focal point and with a first orientation of an x-ray tube of an x-ray device. Subsequently, the x-ray tube is adjusted by rotating about a predetermined angle and by positioning, wherein the focal point is situated in the predetermined position prior to the adjustment and after the adjustment. After the adjustment, the x-ray tube is situated in a second orientation. Subsequently, a second x-ray image is acquired at the predetermined position and with the second orientation. A combined x-ray image from at least the first and second x-ray image is produced.

Method for imaging by means of an X-ray device and X-ray device

A computer-implemented method for identifying features in 3D image volumes includes dividing a 3D volume into a plurality of 2D slices and applying a pre-trained 2D multi-channel global convolutional network (MC-GCN) to the plurality of 2D slices until convergence. Following convergence of the 2D MC-GCN, a plurality of parameters are extracted from a first feature encoder network in the 2D MC-GCN. The plurality of parameters are transferred to a second feature encoder network in a 3D Anisotropic Hybrid Network (AH-Net). The 3D AH-Net is applied to the 3D volume to yield a probability map;. Then, using the probability map, one or more of (a) coordinates of the objects with non-maximum suppression or (b) a label map of objects of interest in the 3D volume are generated.

3D anisotropic hybrid network: transferring convolutional features from 2D images to 3D anisotropic volumes

A method ascertains a time for a fresh calibration for ascertaining up-to-date calibration parameters of an x-ray device. The x-ray device has multiple degrees of freedom of movement for its recording arrangement. X-ray images of a calibration phantom are recorded for recording positions of the recording arrangement and are evaluated to ascertain the calibration parameters allowing ascertainment of geometry parameters. In multiple operating phases, situated between two calibrations, of a further x-ray device of identical design to the x-ray device, a piece of use information describing the accumulated use of the degrees of freedom of movement during the operating phase and a piece of difference information describing the difference in the calibration parameters between the calibrations delimiting the operating phase, is ascertained and used or determining the time for a fresh calibration.

Method for ascertaining a time for a calibration, x-ray device and computer program

A method for the automatic generation of synthetic projections of an examination object from at least one three-dimensional data set acquired by way of a medical imaging system. The three-dimensional data set is used as a basis for determining position information relating to the arrangement of structures of the examination object and at least one synthetic projection based on the position information. We also describe a projection-image-ascertaining facility for the automatic generation of synthetic projections and a computer program product for executing the method.

Method and device for the automatic generation of synthetic projections

A method is provided for the automatic determination of at least one joint load information item concerning a joint of a patient, wherein at least one image data set of the loaded joint is recorded by an imaging apparatus. Several image data sets of the joint, of which at least one is three-dimensional, are recorded in each case for different loading states by the imaging apparatus. By combined evaluation of the image data sets, the at least one joint load information item is determined.

Automatic determination of joint load information

A method automatically evaluates x-ray image data from an examination region of a patient. X-ray image data is received from the examination region. Furthermore x-ray image data is segmented and anatomical structures are detected in the individual segments. In addition reference image data that comes closest to the segmented x-ray image data is determined. This process is undertaken on the basis of a comparison of the segmented x-ray image data with reference image data from a reference database. The reference image data of the reference database has quality information relating to the image quality of the reference image data in each case. Finally a decision is made on the basis of the quality information of the established reference image data as to whether the received x-ray image data is to be retained or rejected.

Automated image evaluation in x-ray imaging

A method of performing digital tomosynthesis includes the steps of obtaining an initial volume (I) formed with a plurality of slices (); performing edge detection in a slice (); processing the detected edges () to obtain a weighting volume (W); and generating a composite slab (S, S) on the basis of the weighting volume (W).

Method and system for computing digital tomosynthesis images

A method for planning an examination of an examination object by a tomosynthesis machine includes: Raw data of the examination object are acquired from defined acquisition angles. An auxiliary data set is reconstructed from the raw data. Depth data are calculated based on the auxiliary data set calculating a number of projections from the perspective of a respectively defined projection center from the auxiliary data set or from the raw data. Each of the projections has a number of image points each linked with associated depth data. The projections are displayed and at least one projection is chosen. A position of an examination region of the examination object is marked therein. A real three-dimensional position of the examination region is calculated using the marked position and its depth data, and an examination path to the examination region is calculated.

Method of planning an examination, method of positioning an examination instrument, tomosynthesis system and computer program product

Data of a predetermined volume portion of an object under examination is captured by an x-ray system that includes an x-ray source and a detector. The x-ray source is activated to generate x-rays that emerge from the x-ray source, radiate through the volume portion, and after radiating through, impinge on the detector. X-rays impinging on the detector are captured pixel by pixel, in order to capture the data of the predetermined volume portion. With the pixel-by-pixel capture, only a subset of all the pixels of the detector is evaluated.

Accelerated data capture in an x-ray system

An operating method assists a diagnosing practitioner with describing the location of a target structure in a tomosynthesis image data record of a compressed breast of a patient. The target structure is localized by a first spatial information item. The method includes: a) ascertaining a first shape information item describing at least one first, compressed breast shape in the tomosynthesis image data record, b) determining a second shape information item describing the breast in a non-compressed breast shape, from the first shape information item, c) mapping the position of the target structure from the compressed breast shape and to the non-compressed breast shape using at least the second shape information item for ascertaining a second spatial information item relating to the non-compressed breast shape, and d) transforming the second spatial information item into a pictogram information item facilitating an abstracted pictorial representation and/or describing the latter.

Method and apparatuses for assisting a diagnosing practitioner with describing the location of a target structure in a breast

A method for generating a combined projection image from a medical inspection object, includes steps of capturing a set of initial projection images; reconstructing a first and a second three-dimensional volume from the set of initial projection images; generating a first re-projection image from the first three-dimensional volume and a second re-projection image from the second three-dimensional volume; weighting the first re-projection image and the second re-projection image; and combining the weighted first re-projection image and second re-projection image for generating the combined projection image.

Method for generating a combined projection image and imaging device

A method for generating a synthetic two-dimensional mammogram with enhanced contrast for structures of interest includes acquiring a three-dimensional digital breast tomosynthesis volume having a plurality of voxels. A three-dimensional relevance map that encodes for the voxels the relevance of the underlying structure for a diagnosis is generated. A synthetic two-dimensional mammogram is calculated based on the three-dimensional digital breast tomosynthesis volume and the three-dimensional relevance map.

Generating a synthetic two-dimensional mammogram

A method of assigning first localization data of a breast of a patient derived from first image data of the breast, the first image data being the result of a first radiological data acquisition process, to second localization data of the same breast derived from second image data, the second image data being the result of a second radiological data acquisition process, or vice versa. Thereby, the first localization data are assigned to the second localization data by intermediately mapping them into breast model data representing a patient-specific breast shape of the patient and then onto the second image data&#x2014;or vice versa, thereby deriving assignment data. An assignment system performs the above-described method.

Imaging device, assignment system and method for assignment of localization data

A method for generating a projection image from tomographic images first captures (S) a number of stacked two-dimensional tomographic images representing a tomographic volume. The pixels of the stacked two-dimensional tomographic images are weighted (S) along a number of projection beams through the tomographic volume with weighting factors that are chosen under the constraint that the sum of all squared weighting factors for each individual projection beam is between a given lower limit and a given upper limit. Then the weighted pixels are summed up (S) along the number of projection beams for generating the two-dimensional projection image.

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Hausen, Germany

Anna Jerebko