Walter H. Backes

This study compares denoising methods for multi-echo 7T fMRI data, finding that ME-ICA combined with aCompCor and ICA-AROMA is highly effective for noise reduction and signal preservation.

This study compares manual and automated quality control strategies for brain MRI segmentation, finding that Euler numbers and MRIQC provide reliable and efficient methods to reduce measurement error.

The paper examines how MRI image quality affects brain connectivity measures and finds that low quality metrics like SNR and motion reduce connectivity, impacting associations with age, sex, and BMI.