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This step maximized the accuracy of registration of each subject's FA map to ICBM152 T2 space, based on three registration landmarks selected to maximize registration in our a priori areas of evaluation (AOEs) (see Text S1).
Each scan was measured based on reliable bone and mucosa landmarks selected to assess the nasal region, as described by Aslan et al. and Contencin et al., and to obtain the measurements of clinically vital distances [ 1, 4].
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Landmarks are selected to participate either as active or passive.
The landmarks were selected to maximise variation among individuals.
Landmarks were selected to represent clearly homologous points, such as suture junctions or extreme points of curvature, and to fully sample the morphology of the entire skull.
Comparing the adding up sum of accumulated familiarity scores of the ten landmarks, (w_1) will be selected to be assigned the task.
A set of homologous landmarks [ 27] was selected to best capture shape variation in each species (additional file 1).
When image features are selected to be new landmarks or moving objects, the inverse depth parameterization vector in Equation (13) is assigned to be new augmented states in the EKF-based SLAM.
Sixty Planetlab nodes were selected to be used as landmarks.
Visual landmarks selected via the proposed method enable mobile robots to identify location using densely packed knowledge.
Thompson et al. [10] proposed the use of landmarks selected automatically from panoramic images.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com