Toshiba Medical Systems Corporation

Canon Medical Systems Corporation

The University of Edinburgh

Keith Goatman

Owen Anderson

James Sloan

Ian Poole

Aneta Lisowska

Sean Daniel Murphy

Alison O'Neil

Mohammad Dabbah

Chengjia Wang

Scott Semple

An apparatus comprises processing circuitry configured to receive a plurality of training image data sets and a plurality of predetermined displacements. The processing circuitry is further configured to use the training image data sets and predetermined displacements to train a transformation regressor in combination with a discriminator in an adversarial fashion by repeatedly alternating a transformation regressor training process in which the transformation regressor is trained to predict displacements, and a discriminator training process in which the discriminator is trained to distinguish between predetermined displacements and displacements predicted by the transformation regressor.

Registration method and apparatus

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 comprises processing circuitry configured to receive first image data; receive second medical image data; and apply a transformation regressor to perform a registration process to obtain a predicted displacement that is representative of a transformation between the first image data and the second image data; wherein the transformation regressor is trained in combination with a discriminator in an adversarial fashion by repeatedly alternating a transformation regressor training process in which the transformation regressor is trained to predict displacements, and a discriminator training process in which the discriminator is trained to distinguish between predetermined displacements and displacements predicted by the transformation regressor.

There is provided an apparatus comprising processing circuitry configured to: receive first medical image data obtained using a first type of imaging procedure, wherein the first medical image data is representative of an anatomical region of a subject; and apply a simulator to perform a simulation process on the first medical image data to obtain simulated second medical image data, the simulated second medical image data having properties so as to simulate image data that is obtained using a second type of imaging procedure. The simulator comprises an image synthesizer that is trained in combination with a discriminator in an adversarial fashion by repeatedly alternating an image synthesizer training process in which the image synthesizer is trained to produce simulated medical image data, and a discriminator training process in which the discriminator is trained to distinguish between real medical image data and simulated medical image data.

Apparatus and method for medical image processing

A medical image processing apparatus comprises a memory configured to store medical image data representative of a tissue structure and a processing circuitry configured to operationally connect to the memory, extract regions from the medical image data by performing threshold processing of the medical image data using each of a plurality of threshold values, select regions meeting at least one predetermined condition from among the extracted regions, and determine a region representative of the tissue structure in the medical image data based on the selected regions.

Medical image processing apparatus and method

A medical imaging data processing apparatus comprises a receiving unit configured to receive first medical imaging data that represents a region of a subject at a first time, and second medical imaging data that represents the region of the subject at a second, later time, a registration unit configured to perform a registration procedure to obtain registration data representative of a registration between the first medical imaging data and the second medical imaging data, an evaluation unit configured to process the registration data to determine, for each of a plurality of positions in the region, a value of a registration measure, the registration measure representing at least one feature of the registration as a function of position, wherein the evaluation unit is configured to, for at least some of the plurality of positions in the region, determine whether an abnormality is present by comparing the value of the registration measure to a statistical atlas.

Medical image data processing apparatus and method for determining the presence of an abnormality

An apparatus for registering medical image data representing a tubular structure comprises a data processing unit for obtaining first medical image data representing the tubular structure and second medical image data representing the tubular structure, a region identification unit for identifying the tubular structure in the first medical image data, defining in the first medical image data a volumetric region of interest comprising the tubular structure along the length of the tubular structure and defining a subset of the first medical image data corresponding to the region of interest, and a registration unit for performing a registration of the subset of the first medical image data with at least some of the second medical image data, wherein the registration comprises at least one of a rigid registration and an affine registration.

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Edinburgh, United Kingdom

Keith Goatman