Photometry for scalp morphology estimation for optical functional neuroimaging

Abigail L. Magee, Calamity Svoboda, Alvin S. Agato, Ed Richter, Joseph P. Culver, Adam T. Eggebrecht

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationNeural Imaging and Sensing 2022
EditorsQingming Luo, Jun Ding, Ling Fu
PublisherSPIE
ISBN (Electronic)9781510647633
DOIs
StatePublished - 2022
EventNeural Imaging and Sensing 2022 - Virtual, Online
Duration: Feb 20 2022Feb 24 2022

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume11946
ISSN (Print)1605-7422

Conference

ConferenceNeural Imaging and Sensing 2022
CityVirtual, Online
Period02/20/2202/24/22

Keywords

  • algorithm
  • brain
  • data registration
  • diffuse optical tomography
  • fNIRS
  • head modeling
  • human
  • photometry

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