Siemens Healthineers Ag

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Gerardo Hermosillo Valadez

Yoshihisa Shinagawa

Simon Allen-Raffl

Mahesh Ranganath

Matthias Wolf

Anna Jerebko

Katharina Schmidler Burk

Shaika Chowdhury

Michael Rusitska

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

There is disclosed a method and apparatus for annotating a first portion of medical imaging data with one or more words corresponding to a respective one or more features represented in the first portion of medical imaging data. A similarity metric indicating a degree of similarity between the first portion and each of a plurality of second portions of reference medical imaging data is determined, at least one of the plurality of second portions being annotated with one or more first words corresponding to a respective one or more features represented in the second portion. A second portion is selected based on the similarity metrics, and the first portion is annotated with the one or more first words with which the second portion, selected for the first portion, is annotated.

Method and apparatus for annotating a portion of medical imaging data with one or more words

A framework for processing medical images. The framework may include receiving a target medical image, a reference medical image and at least one marker associated with a location in the reference medical image. A corresponding location of the at least one marker is determined in the target medical image. The target medical image is overlaid with the at least one marker at the determined corresponding location to provide an overlaid image. Display data is generated to cause a display device to display the overlaid image.

Method for processing medical images

A framework for segmenting a medical text report into sections is disclosed. For each sentence of the report, a first sentence representation is determined by inputting a word-level context representation for each sentence sequentially into a neural network. A second sentence representation is determined by inputting an aggregated representation for each sentence sequentially into another neural network. For each sentence, a third sentence representation is determined based on a combination of the first and second sentence representations, and a section classification for the sentence is determined by inputting the third sentence representation into a section classifier. Each sentence is assigned the section classification determined for the sentence.

Method and apparatus for segmenting a medical text report into sections

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.

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Carmel, IN, United States of America

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