Canon Medical Systems Corporation

The University of Edinburgh

Kabushiki Kaisha Toshiba

Toshiba Medical Systems Corporation

Alison O'Neil

Aneta Lisowska

Ian Poole

Owen Anderson

Sotirios Tsaftaris

Brian Mohr

Keith Goatman

Colin John Roberts

Paul Norman

Grzegorz Jacenków

Matus Falis

Antanas Kascenas

Spyridon Thermos

An apparatus for training a model to identify abnormal medical/image data comprises processing circuitry configured to:

Data processing apparatus for training a model with abnormal medical image data to identify abnormal medical image data

An image data processing apparatus comprises processing circuitry configured to:

Image data processing apparatus and method, a model training apparatus and a training method

An apparatus for medical text processing comprises processing circuitry configured to: obtain a trained model, wherein the trained model is trained to classify medical text documents with a medical classification code; apply the trained model to at least one medical text document to obtain weightings for text terms included in the at least one medical text document, wherein the weightings are associated with the medical classification code; and use the weightings to perform a searching or indexing process.

Text processing apparatus and method

A medical image data processing apparatus is provided and includes processing circuitry to receive medical image data in respect of at least one subject; receive non-image data; generate a filter based on the non-image data; and apply the filter to the medical image data, wherein the filter limits a region of the medical image data.

Data processing apparatus and method

A medical system comprises processing circuitry configured to: receive a first trained model, wherein the trained model has been trained using a first data set acquired in a first cohort; receive a second data set acquired in a second cohort; input data included in the second data set and data representative of the first trained model into a second trained model; and receive from the second trained model an affinity-relating value which represents an affinity between the data included in the second data set and the first trained model.

A medical image processing apparatus includes processing circuitry configured to apply a first trained model to input image data to obtain a first output based on the input data, where the input data includes clinical data. The processing circuitry is further configured to apply a second trained model to the input data to obtain a second output based on the input data, where the first trained model and the second trained model have been trained in dependence on a hierarchical relationship between the first output and the second output. The hierarchical relationship includes at least one of: a spatial hierarchy, a temporal hierarchy, an anatomical hierarchy, and a hierarchy of clinical conditions.

Model training apparatus and method

An apparatus for determining similarity between medical data sets for a plurality of patients or other subjects comprises at least one data store and a processing resource. The at least one data store is configured to store a respective representation of each of a plurality of data sets, the representation of each data set being generated by applying a model for representing data sets with respect to a plurality of features. The processing resource is configured to use the model to obtain a representation of a further medical data set, and perform a similarity determining process to determine similarity between the representation of the further medical data set and at least some of said representations of said plurality of medical data sets.

Similarity determining apparatus and method

A medical image processing apparatus, comprises a landmark identification unit configured to process a medical image data set to identify a landmark corresponding to a part of a branching structure according to a stored anatomical representation, and a spatial analysis unit configured to process the image data set to determine a spatial configuration of at least part of the branching structure.

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Edinburgh, United Kingdom

Alison O'Neil