Grade prediction of lesions in cerebral white matter using a convolutional neural network.

ABSTRACT: We established a diagnostic method for cerebral white matter lesions using MRI images and examined the relationship between the MRI images and the medical checkup data. There were approximately 25 MRI images for each patient's head, from the top of the head to near the eyes. To order these images, we defined the unit of axial for convenience. We varied conditions, such as the location and extent of the images to be loaded, into a convolutional neural network model and verified the changes in discrimination performance on the test data. Co-occurrence network diagrams were also used to determine the relationship between the grade of cerebral white matter lesions and the biochemical test items, which were treated as categorical variables, the progression of cerebral white matter lesions, and

SUBMITTER: Takemura N 

PROVIDER: S-EPMC11554140 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature