1 research outputs found
Brain Age Estimation Using LSTM on Children's Brain MRI
Brain age prediction based on children's brain MRI is an important biomarker
for brain health and brain development analysis. In this paper, we consider the
3D brain MRI volume as a sequence of 2D images and propose a new framework
using the recurrent neural network for brain age estimation. The proposed
method is named as 2D-ResNet18+Long short-term memory (LSTM), which consists of
four parts: 2D ResNet18 for feature extraction on 2D images, a pooling layer
for feature reduction over the sequences, an LSTM layer, and a final regression
layer. We apply the proposed method on a public multisite NIH-PD dataset and
evaluate generalization on a second multisite dataset, which shows that the
proposed 2D-ResNet18+LSTM method provides better results than traditional 3D
based neural network for brain age estimation.Comment: ISBI 202