FIELD: physics; image processing.
SUBSTANCE: invention can be used for magnetic resonance imaging (MRI) processing. Magnetic resonance imaging (MRI) for generating training data is implemented by a processing device comprising a processor, memory and machine-readable instructions which cause the processor to perform the following steps: receiving magnetic resonance imaging (MRI) images of patients; processing of the obtained images, at which: determining the brightness value of each pixel; calculating the brightness histogram along the Y axis, for which: calculating the brightness of each line by adding the brightness of the pixels of each line, determining the average brightness value for each line; calculating the root-mean-square deviation of brightness of all pixels of a line from the average for the same line and calculating for each line the product of the sum of brightness by the root-mean-square deviation of brightness; calculating a brightness histogram along the X axis, for which: calculating the brightness of each column by adding the brightness of the pixels of each column, determining the average brightness value for each column; calculating the root-mean-square deviation of the brightness of all pixels of the column from the average for the same column and calculating for each column the product of the sum of the brightness by the root-mean-square deviation of brightness; setting threshold values of brightness; excluding on the Y axis lines, the brightness value for which is below the first threshold value, and on the X axis columns, the brightness value for which is below the second threshold value; normalizing the obtained images; outputting the final image to the input of the neural network for training; storing the obtained neural network model on a processing device.
EFFECT: high accuracy of determining anomalies in MRI images.
14 cl, 2 dwg
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Authors
Dates
2024-02-12—Published
2023-10-31—Filed