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These shifted maps are automatically segmented in three areas as well.
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Given the approximate tumour centre location, each index breast tumour was automatically segmented in the three-dimensional (3D) space.
Briefly, T2 hyperintense lesions were automatically segmented in the FLAIR and T2/PD images and visually verified using interactive software to correct misclassifications.
First, the fiducial markers were automatically segmented in the 3D preoperative volume based on knowledge about marker form, size, and attenuation.
Approximately 85 individual cells were automatically segmented and quantified in each image (over 11 million segmented cells in total) and were used to calculate average expression values for each construct over time.
After image capture, all cells within each spot were automatically segmented thanks to detection protocols integrated in Pathfinder™ system.
In addition, LVM was automatically segmented from the CCTA images.
In addition, NFL thickness was automatically segmented per A-scan on all volumes with another method based on adaptive thresholding [ 20– 20].
In addition, the following subcortical structures at both time-points were automatically segmented from each hemisphere using Freesurfer: thalamus, caudate, putamen, pallidum, hippocampus, amygdala, and the nucleus accumbens.
Each training utterance was automatically segmented to have about 30 s of speech.
With the above procedure, the nuclear regions of a 3D DIC volume can be automatically segmented.
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