Brain image processing method, device, readable storage medium and electronic equipment

Abstract

The invention relates to a brain image processing method and device, a readable storage medium and electronic equipment. The method comprises the steps that a target brain image is input into a convolutional neural network, image features of the target brain image are obtained, and the convolutional neural network is generated by training a brain image training sample set; sparse feature extraction is performed on the image features of the target brain image by using a target dictionary model to obtain sparse features of the target brain image; and an image grade corresponding to the target brain image is determined according to the sparse feature of the target brain image, the image grade being used for reflecting the change degree of brain tissue. Thus, the change degree of the brain tissue in the brain image can be intelligently recognized, manual judgment is not needed any more, the brain image recognition difference caused by personal environment, experience and other differencescan be reduced, and then the brain tissue lesion degree judgment accuracy in brain image recognition is improved.

Description

technical field [0001] The present disclosure relates to the field of computer technology, and in particular, to a brain image processing method, device, readable storage medium, and electronic equipment. Background technique [0002] In the medical field, it is often necessary to take images such as brain structure CT, MRI, and FGD PET to show the actual situation of the patient's brain. After the brain structure CT, MRI, FGD PET, etc. are taken, the doctor needs to observe such images to know the current brain condition of the patient, for example, to determine the changes of the patient's brain tissue through the captured images. Can be manifested as changes in brain tissue volume. At present, such changes can only be determined manually by doctors, and due to different personal environments, personal experiences, and personal perspectives, there are often differences in observation results, which will also affect subsequent inspection results. Therefore, the way of hum...

AI Technical Summary

Problems solved by technology

At present, such changes can only be determined manually by doctors, and due to different personal environments, personal experiences, and personal perspectives, there are often differences in observation results, which will also affect subsequent inspection results.

Therefore, the way of human observation is not only labor-intensive, but also has the problem of insufficient accuracy

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