@inproceedings{d12656ba0e2049e9871aa51032a509cb,
title = "Photometry for scalp morphology estimation for optical functional neuroimaging",
abstract = "Image reconstruction with functional near infrared spectroscopy (fNIRS) and high density diffuse optical tomography (HD-DOT) rely on anatomical models that adequately capture the head size and shape for accurate data registration. Optical brain imaging studies in infants and toddlers without MRI present challenges in model generation because individual differences in scalp morphometry across early development lead to poor matches with atlas-based models. Additionally, current photometric methods are limited due to the presence of hair. We present herein the scalp surface estimation technique, validated with participant specific MRI, that accurately provides the head shape in the presence of hair.",
keywords = "algorithm, brain, data registration, diffuse optical tomography, fNIRS, head modeling, human, photometry",
author = "Magee, {Abigail L.} and Calamity Svoboda and Agato, {Alvin S.} and Ed Richter and Culver, {Joseph P.} and Eggebrecht, {Adam T.}",
note = "Publisher Copyright: {\textcopyright} 2022 SPIE.; Neural Imaging and Sensing 2022 ; Conference date: 20-02-2022 Through 24-02-2022",
year = "2022",
doi = "10.1117/12.2608326",
language = "English",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Qingming Luo and Jun Ding and Ling Fu",
booktitle = "Neural Imaging and Sensing 2022",
}