Automatic Segmentation and Skeletonization of Neurons from Confocal Microscope Images based on the 3-D Wavelet Transform

In our first experiment we regress the bread units given the RGB and the corresponding ground-truth depth map obtained from the Kinect using a state-of-the-art Convolu- tional

Motivated by recent findings of patterns of response latencies in mitral/tufted (M/T) cells in the olfactory bulb [23], the present study investigated ORN population responses with

To this end, each ligament will be represented by a number of cylindrical beam elements along the skeleton line (ligament path) with different diameters (ligament shape), see

On each fluoroscopic image, taking the correspondent silhouette of the projected statistical model C k,n model as a template, a Bayesian network based shape matching is implemented

If the components of one class do exhibit some type of connectivity in a different feature space B, where there is also no overlap, then the hysteresis paradigm is used to

On the basis of the computed image background and cell membrane pixels, small regions within probable cells are identified – the cell markers (see Fig.. It is assumed that

Kompsat-3 images are available as L1R images, corresponding close to the original image geometry, and as L1G, being projected to the SRTM 3 arcsec height model.. For use of Semi

The road model used for many line-based approaches is similar to the one described in (Wiedemann, 2002): roads are modelled as long lines with a certain width of a few pixels