Image processing apparatus, operation method of image processing apparatus, operation program of image processing apparatus, and trained model
AssigneeFUJIFILM Corporation
InventorCaihua Wang
Life of this patent
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Abstract
An image processing apparatus includes a processor and a memory connected to or built in the processor. The processor is configured to perform non-linear registration processing on a first medical image and a second medical image among a plurality of medical images, and generate at least one new medical image that is used for training a machine learning model for the medical images by transforming at least one medical image of the first medical image or the second medical image based on a result of the non-linear registration processing.
Claims12
An image processing apparatus comprising:
- a processor;
- and
- a memory connected to or built in the processor,
- wherein the processor is configured to
- perform non-linear registration processing on a first medical image and a second medical image among a plurality of medical images to derive transformation amounts as a result of the non-linear registration processing, wherein the medical images are classified into classes,
- generate transformation coefficients based on the classes of the first medical image and the second medical image,
- multiply the transformation coefficients by the derived transformation amounts to obtain corrected transformation amounts, and
- generate at least one new medical image that is used for training a machine learning model for the medical images by transforming at least one medical image of the first medical image or the second medical image using at least one of the corrected transformation amounts.
An operation method of an image processing apparatus, the method comprising:
- performing non-linear registration processing on a first medical image and a second medical image among a plurality of medical images to derive transformation amounts as a result of the non-linear registration processing, wherein the medical images are classified into classes,
- generating transformation coefficients based on the classes of the first medical image and the second medical image,
- multiplying the transformation coefficients by the derived transformation amounts to obtain corrected transformation amounts;
- and
- generating at least one new medical image that is used for training a machine learning model for the medical images by transforming at least one medical image of the first medical image or the second medical image using at least one of the corrected transformation amounts.
A non-transitory computer-readable storage medium storing an operation program of an image processing apparatus, the program causing a computer to execute a process comprising:
- performing non-linear registration processing on a first medical image and a second medical image among a plurality of medical images to derive transformation amounts as a result of the non-linear registration processing, wherein the medical images are classified into classes,
- generating transformation coefficients based on the classes of the first medical image and the second medical image,
- multiplying the transformation coefficients by the derived transformation amounts to obtain corrected transformation amounts;
- and
- generating at least one new medical image that is used for training a machine learning model for the medical images by transforming at least one medical image of the first medical image or the second medical image using at least one of the corrected transformation amounts.
A non-transitory computer-readable storage medium storing a trained model that is trained by using a new medical image as a learning image, the new medical image being generated by transforming at least one medical image of a first medical image or a second medical image among a plurality of medical images using at least one of corrected transformation amounts, wherein the corrected transformation amounts is obtained by:
- performing non-linear registration processing on the first medical image and the second medical image to derive transformation amounts as a result of the non-linear registration processing, wherein the medical images are classified into classes,
- generating transformation coefficients based on the classes of the first medical image and the second medical image, and
- multiplying the transformation coefficients by the derived transformation amounts to obtain the corrected transformation amounts.
Dependencies are inferred from the claim text.