Fig. 2.

Illustration of the proposed respiratory signal estimation. From the medical image, non-overlapping patches are extracted at multiple resolutions (a). Kernel PCA is applied to each patch leading to a set of low-dimensional embeddings, where each color represents a different dimension. Hierarchical clustering, represented by a dendrogram, finds similar signals (b). The respiratory cluster is identified and the corresponding signals are combined and normalized to give the respiratory signal (c).