Machine Learning-based Estimation of Respiratory Fluctuations in a Healthy Adult Population using BOLD fMRI and Head Motion Parameters

arXiv:2405.00219v1 Announce Type: new
Abstract: Motivation: In many fMRI studies, respiratory signals are often missing or of poor quality. Therefore, it could be highly beneficial to have a tool to extract respiratory variation (RV) waveforms directly from fMRI data without the need for peripheral recording devices.
Goal(s): Investigate the hypothesis that head motion parameters contain valuable information regarding respiratory patter, which can help machine learning algorithms estimate the RV waveform.
Approach: This study proposes a CNN model for reconstruction of …

abstract arxiv bold cs.lg data extract fmri head machine machine learning motivation parameters population quality studies tool type variation