A Domain Guided CNN Architecture for Predicting Age from Structural Brain Images

08/11/2018
by   Pascal Sturmfels, et al.
0

Given the wide success of convolutional neural networks (CNNs) applied to natural images, researchers have begun to apply them to neuroimaging data. To date, however, exploration of novel CNN architectures tailored to neuroimaging data has been limited. Several recent works fail to leverage the 3D structure of the brain, instead treating the brain as a set of independent 2D slices. Approaches that do utilize 3D convolutions rely on architectures developed for object recognition tasks in natural 2D images. Such architectures make assumptions about the input that may not hold for neuroimaging. For example, existing architectures assume that patterns in the brain exhibit translation invariance. However, a pattern in the brain may have different meaning depending on where in the brain it is located. There is a need to explore novel architectures that are tailored to brain images. We present two simple modifications to existing CNN architectures based on brain image structure. Applied to the task of brain age prediction, our network achieves a mean absolute error (MAE) of 1.4 years and trains 30 that achieves a MAE of 1.6 years. Our results suggest that lessons learned from developing models on natural images may not directly transfer to neuroimaging tasks. Instead, there remains a large space of unexplored questions regarding model development in this area, whose answers may differ from conventional wisdom.

READ FULL TEXT
research
12/27/2021

Infant Brain Age Classification: 2D CNN Outperforms 3D CNN in Small Dataset

Determining if the brain is developing normally is a key component of pe...
research
12/23/2021

Predição da Idade Cerebral a partir de Imagens de Ressonância Magnética utilizando Redes Neurais Convolucionais

In this work, deep learning techniques for brain age prediction from mag...
research
07/25/2019

Is Texture Predictive for Age and Sex in Brain MRI?

Deep learning builds the foundation for many medical image analysis task...
research
12/07/2022

Deep Learning for Brain Age Estimation: A Systematic Review

Over the years, Machine Learning models have been successfully employed ...
research
11/24/2020

Insights From A Large-Scale Database of Material Depictions In Paintings

Deep learning has paved the way for strong recognition systems which are...
research
09/14/2021

Identifying partial mouse brain microscopy images from Allen reference atlas using a contrastively learned semantic space

Precise identification of mouse brain microscopy images is a crucial fir...
research
02/01/2023

An Out-of-Domain Synapse Detection Challenge for Microwasp Brain Connectomes

The size of image stacks in connectomics studies now reaches the terabyt...

Please sign up or login with your details

Forgot password? Click here to reset