Figure 4.

Proposed framework for predicting morphological brain age in healthy and disordered brains. (A) Construction of the multi-view brain networks from cortical morphology for each subject and the construction of the initial feature vector. For each subject $k\in \{1,\dots ,N\}$, we derive a morphological network ${ℳ}_k^m$ from the cortical surface $S_k^m$ mapped using a specific morphological attribute $m\in \{1,\dots ,M\}$. (B) Next, we extract the lower triangular part of the matrix as a morphological connectional feature vector. (C) Reduce the dimensionality of the data and retain only the most relevant features using a feature selection method. Next, we train a Random Forest model and utilize it to predict the morphological age of a testing brain. (D) Connectional morphological features encoding chronological brain age.