In Diffuse Optical Tomography (DOT), an atlas-based model can be used as an alternative to a subject-specific anatomical model for recovery of brain activity. The main step of the generation of atlas-based subject model is the registration of atlas model to the subject head. The accuracy of the DOT then relies on the accuracy of registration method. In this work, 11 registration methods are quantitatively evaluated. The registration method with EEG 10/20 systems with 19 landmarks and non-iterative point to point algorithm provides approximately 1.4 mm surface error and is considered as the most efficient registration method.
In MRI-guided diffuse optical tomography of the human brain function, three-dimensional anatomical head model
consisting of up to five segmented tissue types can be specified. With disregard to misclassification between different
tissues, uncertainty in the optical properties of each tissue type becomes the dominant cause of systematic error in image
reconstruction. In this study we present a quantitative evaluation of image resolution dependence due to such uncertainty.
Our results show that given a head model which provides a realistic description of its tissue optical property distribution,
high-density diffuse optical tomography with cortically constrained image reconstruction are capable of detecting focal
activation up to 21.81 mm below the human scalp at an imaging quality better than or equal to 1.0 cm in localization
error and 1.0 cm3 in FVHM with a tolerance of uncertainty in tissue optical properties between +15% and -20%.
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