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US 12,579,648 B2Granted
Methods and systems for identifying slices in medical image data sets
AssigneeSiemens Healthineers AG
InventorsYoshihisa Shinagawa, Halid Yerebakan, Gerardo Hermosillo Valadez, Mahesh Ranganath, Simon Allen-Raffl
Life of this patent
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Abstract
Computer-implemented methods and systems for identifying corresponding slices in medical image data sets are provided. For example, the systems and methods are based on identifying corresponding slices by systematically quantifying image similarities between the slices comprised in one medical image data set and the slices comprised in another medical image data set.
Claims15
A computer-implemented method comprising:
- receiving a first medical image data set;
- extracting at least one image descriptor from image data of the first medical image data set, the at least one image descriptor from the image data of the first medical image data set being a first feature vector;
- receiving a second medical image data set, the second medical image data set including a plurality of slices and being different from the first medical image data set;
- extracting at least one image descriptor from each slice of the plurality of slices of the second medical image data set, the at least one image descriptor from each slice of the plurality of slices of the second medical image data set being a second feature vector;
- comparing, with a trained function, the at least one image descriptor of the first medical image data set and the at least one image descriptor from each slice of the plurality of slices of the second medical image data set to generate a degree of similarity between the first medical image data set and each slice of the plurality of slices of the second medical image data set;
- and
- identifying, from the plurality of slices of the second medical image data set, at least one corresponding slice based on the degrees of similarity between the first medical image data set and each slice of the plurality of slices of the second medical image data set, wherein
- the trained function is configured to determine degrees of similarity between two-dimensional medical images, and
- the trained function applies a learned metric to determine the degrees of similarity between the two-dimensional medical images, the trained function including a deep metric learning network.
6 more elements
A system comprising:
- an interface configured to receive a first medical image data set and a second medical image data set, the second medical image data set including a plurality of slices and being different from the first medical image data set;
- and
- a computing unit configured to cause the system to,
- extract at least one image descriptor from image data of the first medical image data set, the at least one image descriptor from the image data of the first medical image data set being a first feature vector,
- extract at least one image descriptor from each slice of the plurality of slices of the second medical image data set, the at least one image descriptor from each slice of the plurality of slices of the second medical image data set being a second feature vector,
- compare, with a trained function, the at least one image descriptor of the first medical image data set and the at least one image descriptor from each slice of the plurality of slices of the second medical image data set to generate a degree of similarity between the first medical image data set and each slice of the plurality of slices of the second medical image data set, and
- identify, from the plurality of slices of the second medical image data set, at least one corresponding slice based on the degrees of similarity between the first medical image data set and each slice of the plurality of slices of the second medical image data set, wherein
- the trained function is configured to determine degrees of similarity between two-dimensional medical images, and
- the trained function applies a learned metric to determine the degrees of similarity between the two-dimensional medical images, the trained function including a deep metric learning network.
6 more elements
Dependencies are inferred from the claim text.