Inference of cartilage segmentation in computed tomography scans
AssigneesSmith & Nephew, Inc., Smith & Nephew Orthopaedics AG, Smith & Nephew Asia Pacific Pte. Limited
InventorsMichel Goncalves ALMEIDA ANTUNES, Miguel MARQUES, João Pedro DE ALMEIDA BARRETO, Carolina DOS SANTOS RAPOSO
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Abstract
Some examples are directed to a processor-implemented methods of training a neural network for soft-tissue labeling of computed tomography (CT) images, neural networks trained according to one or more of the processor-implemented methods, processor-implemented methods of soft-tissue-labeling a CT image, and systems for labeling soft-tissue in computed tomography images.
Claims20
A processor-implemented method of training a neural network for soft-tissue labeling comprising:
- creating a training set of soft-tissue-labeled computed tomography (CT) images comprising:
- collecting, from at least one database, pairs of images for each of a plurality of individuals, each pair comprising both a CT image of an individual's anatomy and a magnetic resonance (MR) image of the individual's anatomy;
- and
- for each of the pairs:
- generating a 2D transformation between bone in the MR image and bone in the CT image;
- labeling soft-tissue in the CT image based on an application of the 2D transformation to labeled soft-tissue in the MR image, thereby to create a soft-tissue-labeled CT image;
- and
- augmenting the training set with the soft-tissue-labeled CT image;
- and
- training the neural network using the training set to label soft-tissue in CT images.
A processor-implemented method of soft-tissue labeling an input CT image of an individual's anatomy comprising:
- generating, by a neural network based on the input CT image, a respective output synthetic magnetic resonance (MR) image of the individual's anatomy, wherein the neural network is trained using a generative adversarial approach, using at least CT training images and MR training images, to receive CT images of individuals' anatomy and generate respective output synthetic MR images of the individuals' anatomy;
- receiving at least soft-tissue labeling corresponding to the respective output synthetic MR image;
- and
- applying at least the soft-tissue labeling from the respective output synthetic MR image to the input CT image thereby to soft-tissue label the input CT image.
Dependencies are inferred from the claim text.