Automated

Description

This plugin converts all occurrences of red in a red/green image with magenta, effectively replacing it with a magenta/green merge.

Note: the plugin completely ignores the blue channel, and replaces it with a copy of the red channel.

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Description

Align two images using intensity correlation, feature matching, or control point mapping

Together, Image Processing Toolbox™ and Computer Vision Toolbox™ offer four image registration solutions: interactive registration with a Registration Estimator app, intensity-based automatic image registration, control point registration, and automated feature matching. 

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Description

Wolfram Mathematica (usually termed Mathematica) is a modern technical computing system spanning most areas of technical computing — including neural networksmachine learningimage processinggeometrydata sciencevisualizations, and others. The system is used in many technical, scientific, engineering, mathematical, and computing fields.

Description

FastSME: Faster and Smoother Manifold Extraction From 3D Stack.

3D image stacks are routinely acquired to capture data that lie on undulating 3D manifolds yet processed in 2D by biologists. Algorithms to reconstruct the specimen morphology into a 2D representation from the 3D image volume are employed in such scenarios. In this paper, we present FastSME, which offers several improvements on the baseline SME algorithm which enables accurate 2D representation of data on a manifold from 3D volumes, however is computationally expensive. The improvements are achieved in terms of processing speed (3X-10X speed-up depending on image size), minimizing sensitivity to initialization, and also increases local smoothness of the recovered manifold resulting in better reconstructed 2D composite image. We compare the proposed FastSME against the baseline SME as well as other accessible state-of-the-art tools on synthetic and real microscopy data. Our evaluation on multiple metrics demonstrates the efficiency of the presented method in maintaining fidelity of manifold shape and hence specimen morphology.

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