Image quality analysis of high-density diffuse optical tomography incorporating a subject-specific head model

Yuxuan Zhan, Adam T. Eggebrecht, Joseph P. Culver, Hamid Dehghani

Research output: Contribution to journalArticle

46 Scopus citations

Abstract

High-density diffuse optical tomography (HD-DOT) methods have shown significant improvement in localization accuracy and image resolution compared to traditional topographic near infrared spectroscopy of the human brain. In this work we provide a comprehensive evaluation of image quality in visual cortex mapping via a simulation study with the use of an anatomical head model derived from MRI data of a human subject. A model of individual head anatomy provides the surface shape and internal structure that allow for the construction of a more realistic physical model for the forward problem, as well as the use of a structural constraint in the inverse problem. The HD-DOT model utilized here incorporates multiple source-detector separations with continuous-wave data with added noise based on experimental results. To evaluate image quality we quantify the localization error and localized volume at half maximum (LVHM) throughout a region of interest within the visual cortex and systematically analyze the use of whole-brain tissue spatial constraint within image reconstruction. Our results demonstrate that an image quality with less than 10mm in localization error and 1000 m 3 in LVHM can be obtained up to 13mm below the scalp surface with a typical unconstrained reconstruction and up to 18mm deep when a whole-brain spatial constraint based on the brain tissue is utilized.

Original languageEnglish
Article number6
JournalFrontiers in Neuroenergetics
Issue numberMAY
DOIs
StatePublished - Jun 11 2012

Keywords

  • Functional monitoring and imaging
  • Image reconstruction techniques
  • Tomography

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