Image feature detection

Six 2D differential operations are implemented in this ImageJ plugin. - Gradient Magnitude - Gradient Direction - Laplacian - Largest Hessian - Smallest Hessian - Hessian Orientation

 Fast edge and ridge detection, irrespective of their orientation.

Automatic finding of image features are very convenient for registering two images to align them in proper orientation. Two image plugins are implemented for extracting image features and are placed as menu items at: [Plugins > Feature Extraction > Extract SIFT Correspondences] and [Plugins > Feature Extraction > Extract MOPS Correspondences].

For more details, see the linked page in Fiji wiki. For details about SIFT algorithm, see 2569. For more details about MOPS algorithm, see 2570.

The Sholl technique is used to describe neuronal arbors. This plugin can perform Sholl directly on 2D and 3D grayscale images of isolated neurons. Its internal algorithm to collect data is based upon how Sholl analysis is done by hand — it creates a series of concentric shells (circles or spheres) around the focus of a neuronal arbor, and counts how many times connected voxels defining the arbor intersect the sampling shells. The major advantages of this plugin over other implementations are:

• When analyzing images directly, it does not require previous tracing of the arbor (although it can also analyze traced arbors)
• It combines curve fitting with several methods to automatically retrieve quantitative descriptors from sampled data, which allows direct statistical comparisons between arbors
• It allows continuous and repeated sampling around user-defined foci
• It allows batch processing

This plugin permit to measure the signal spread of a molecule with respect to the cell area.