Linux

A complete package for fluorescence lifetime analysis implemented as an R package with sample data.

The wound healing tool measures the area of a wound in a time series of images of cellular tissue. The tool will measure the area of the wound, i.e. the area that does not contain tissue, in each image. The segmentation is based on the fact that the image is more homogeneous in the region of the wound as in the region of the tissue. Via the options, one of two methods to detect the empty area, can be selected. The first uses edge detection, the second a variance filter. Holes in the detected tissue are filled using morphological operations.

The skin tools measure the thickness of the epidermis and the interdigitation index.

The input images are masks that represent the epidermis and that have been created from images of stained histological sections. The mask must touch the left and right border of the image. The dermal-epidermal border must be on the lower site of the image. The interdigitation index can be measured for one or more segments per image. As a measure of the thickness of the epidermis the lengths of a number of random line segments are measured. The line segments start at the lower border, are perpendicular to the lower border and end at the opposite border of the mask.

See installation Instructions on the website.

nctuTW is a "high-throughput computer method of reconstructing the neuronal structure of the fruit fly brain. The design philosophy of the proposed method differs from those of previous methods. We propose first to compute the 2D skeletons of a neuron in each slice of the image stack. The 3D neuronal structure is then constructed from the 2D skeletons. Biologists tend to use confocal microscopes for optimal images in a slice for human visualization; and images in two consecutive slices contain overlapped information. Consequently, a spherical object becomes oval in the image stack; that is, neurons in the image stack do not reflect the true shape of the neuron. This is the main reason we chose not to work directly on the 3D volume.

The proposed method comprises two steps. The first is the image processing step, which involves computing a set of voxels that is a superset of the 3D centerlines of the neuron. The shortest path graph algorithm then computes the centerlines. The proposed method was applied to process more than 16 000 neurons. By using a large amount of reconstructions, this study also demonstrated a result derived from the reconstructed data using the clustering technique." (Extracted from reference publication)

Illustrative image shows gold standard (top) and method results (bottom).