The myocardial epicardial surfaces were identified in the reformatted CTA and MR data sets using a 3D semi-automated segmentation algorithm.

The developed methodology allows rapid quantification of three-dimensional datasets by semi-automated segmentation of fluorescently labeled objects with conventional computer hardware.

Semi-automated segmentation followed by manual segmentation had the highest correlation between measured and true tumor volume for all 3 tumor geometries.

The perimeter of the cell slices was measured in the TEM images using a semi-automated segmentation into background, cytoplasm and nucleus.

White matter and gray matter lesion volumes were measured in each hemisphere using a semi-automated segmentation process and compared against depression status.

This work presents a reliable and effective two-dimensional semi-automated segmentation technique that uses the encoded motion to project a manually-defined region of interest through time.