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Manual segmentation has become more and more time consuming with the increasing amount of patient data.
This statistic demonstrates that the manual segmentation has no confidence in tracking the tumor volume during the patient follow-up process and the automatic methods that could achieve a sufficient level of accuracy would be highly desirable for their ability to perform high-throughput segmentation.
Manual segmentation has been employed in previous OCT studies with RP patients [ 9– 12].
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A template database of high quality 3T scans and bilateral manual segmentations was created by a neurologist (GW) and radiographer (EW) reviewing the scans sequentially until 400 scans without artifacts (e.g., motion) and with reliable manual segmentations had been selected.
Manual hippocampal segmentation has been shown to be as or more reliable than auto-segmentation algorithms; however, our protocol of editing auto-segmented files for smoothness would need validation with a large number of patients and controls, and work-intensive manual segmentation is impractical on a large scale [14].
The manual segmentation procedure has been previously described [ 12, 13].
Manual segmentation protocols have been published previously.
The ensuing segmentation has reshaped politics.
3D segmentation has slightly lower sensitivity compared to 2D segmentation.
After visual checking of every delineation (by KH and CRL), manual correction of the breast segmentation had to be carried out in approximately 10% of the images.
Compared to manual segmentation, the method used has the advantage that its segmentation is based on voxel intensities, while in manual segmentation the contrast differences can be difficult to detect visually.
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