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After two washing steps, images of the arrays were acquired with the Agilent scanner and analyzed by using the Feature Extraction software (v9.1).
Even after the above processing steps, images with no visible PCO and in which PCO would not be expected still showed on histogram analysis to have image areas with low but significant intensities of up to 15 units of brightness that contributed to elevated entropy scores.
Normalization was performed in 2 steps: images were first aligned with stereotactic axes and then transformed to the Talairach grid using a piecewise affine transformation based on manual identification of the anterior and posterior commissure and the edges of cortex along each axis.
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The framework consists of two steps: image shadow removal and tracking by association.
The usual workflow includes two distinct steps: image acquisition with UAV and computationally demanding post-flight image processing.
This approach mainly includes three steps: image segmentation, feature extraction, and classification.
In this case, LCD becomes an image matching problem, which typically includes two steps, image description and similarity measurement.
The algorithm has four main steps: image preprocessing, initial left ventricular chamber detection, left ventricular chamber center detection and left ventricular endocardial boundary detection.
Unfortunately, this accuracy is compromised due to errors introduced by each of the building steps: image acquisition, segmentation, triangulation, printing and infiltration.
Test has been executed in three steps: image acquisition by camera, TV screen content extraction and full-reference image quality assessment.
The paradigm of computational stereo [1] is that it proceeds following six major steps: image acquisition, camera modeling, feature acquisition, image matching, distance or depth determination, and interpolation.
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CEO of Professional Science Editing for Scientists @ prosciediting.com