In this study, we used deep learning model to estimate the age of children based on the MR signal changes associated with myelination process on T1 and T2-weighed images. Brain MR images of 119 children age ranging from 0.25 to 24 months were first used as a training and test dataset. The age was then estimated by deep learning model based on the T1-WI and T2-WI dataset and T1-WI only dataset. Our results showed that convolution neural network model using T1WI and T2WI dataset demonstrated higher correlation and lower mean absolute error (MAE) compared to T1-WI only dataset.
This abstract and the presentation materials are available to members only; a login is required.