Siemens Healthineers Ag

Siemens Healthcare Gmbh

Anna Jerebko

Dorin Comaniciu

Shaohua Kevin Zhou

Sasa Grbic

Thomas Mertelmeier

Gerardo Hermosillo Valadez

Yoshihisa Shinagawa

Daguang Xu

Halid Yerebakan

Marcus Radicke

Wolfgang Neuber

Matthias Wolf

Mario Bechtold

Ludwig Ritschl

Olivier Pauly

Siqi Liu

Parmeet Singh Bhatia

Julia Wicklein

Juliane Ritter

Yu Zhao

Helmut Gollwitzer

Simon Allen-Raffl

Mahesh Ranganath

Halid Ziya Yerebakan

Yiyuan Zhao

Ann-Christin Roessler

Karin Ratzmer

Anja Brundobler

Daniela Bolte

Katharina Schmidler Burk

A computer implemented method and apparatus for determining a location at which a given feature is represented in medical imaging data is disclosed. A first descriptor for a first location in first medical imaging data is obtained. The first location is the location within the first medical imaging data at which the given feature is represented. A second descriptor for each of a plurality of candidate second locations in second medical imaging data is obtained. A similarity metric indicating a degree of similarity with the first descriptor is calculated for each of the plurality of candidate second locations. A candidate second location is selected from among the plurality of candidate second locations based on the calculated similarity metrics. The location at which the given feature is represented in the second medical imaging data is determined based on the selected candidate second location.

Determining a location at which a given feature is represented in medical imaging data

One or more example embodiments of the present invention relates to a computer-implemented method for providing an outline of a lesion in digital breast tomosynthesis includes receiving input data, wherein the input data comprises a reconstructed tomosynthesis volume dataset based on projection recordings, a virtual target marker within a lesion being in the tomosynthesis volume dataset; applying a trained function to at least a part of the tomosynthesis volume dataset to establish an outline enclosing the lesion, the part of the tomosynthesis volume dataset corresponding to a region surrounding the virtual target marker in the tomosynthesis volume dataset; and providing output data, wherein the output data is an outline of a two-dimensional area or a three-dimensional volume surrounding the target marker.

Computer-implemented method for providing an outline of a lesion in digital breast tomosynthesis

Method and apparatus for image retrieval. An image descriptor of a query image indicating a medical abnormality and non-image patient data may be received. For each of a plurality of candidate images stored in a database, an image descriptor of the candidate image and data about a medical abnormality known to be indicated by the candidate image may further be received. A similarity metric between the image descriptors of the query image and the candidate image may be determined for each candidate image. A first probability of the query image medical abnormality being the candidate image medical abnormality given the non-image patient data associated with the query image may be determined for each candidate image. A score may then be determined for each candidate image based on the determined similarity metric and the determined first probability. One or more of the candidate images may be retrieved from the database in accordance with the determined scores.

Image retrieval

A computer-implemented method is for classifying a region of interest in a medical image data set depicting a body part of a patient. The region of interest contains an object of potential pathological relevance. In an embodiment, the method includes a plurality of steps. One step is directed to generate a plurality of different representations of the region of interest. Another step is directed to determine, for each of the representations, a classification to generate a corresponding plurality of classifications. Thereby, each classification indicates a pathological relevance of the object in the respective representation. Yet, a further step is directed to calculate an ensemble classification for the region of interest based on the plurality of classifications.

Method and system for computer aided detection of abnormalities in image data

A system and a method are respectively for positioning an examination object and evaluation of an image with respect to a positioning of a breast of an examination object in relation to an x-ray device. In an embodiment, the system includes an x-ray device including at least one compression device to fix a breast of the examination object; at least one camera, arranged in relation to the x-ray device such that images are acquirable via the at least one camera, the images showing a current positioning of the breast of the examination object in relation to the x-ray device; and at least one display device, embodied to display the images.

Positioning of an examination object in relation to an x-ray device

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Paoli, PA, United States of America

Anna Jerebko