Multimodal imaging

Utilizing different imaging modalities in combination

Description

Epina ImageLab is a Microsoft Windows-based multisensor imaging tool for processing and analyzing hyperspectral images. It is a modular system consisting of a basic engine, a graphical user interface, a chemometrics toolbox and optional user-supplied modules. It supports the most important spectroscopic imaging techniques, such as UV/Vis, infrared, Raman, THz, optical emission/absorption, and mass spectrometry. On top of that Epina ImageLab enables the user to merge hyperspectral images with maps of physical properties and conventional high-resolution color photos. 

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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

Dragonfly is a software platform for the intuitive inspection of multi-scale multi-modality image data. Its user-friendly experience translates into powerful quantitative findings with high-impact visuals, driven by nuanced easy-to-learn controls.

For segmentation: It provides an engine fior machine Learning, Watershed and superpixel methods, support histological data .

It offers a 3D viewer, and python scripting capacities .

It is free for reserach use, but not for commercial usage.

DragonFly
Description

The project introduces a cross-platform framework for comparison of image registration methods with landmark validation (registration precision is measured by user landmarks). The project contains a set of sample images with related landmark annotations and experimental evaluation of state-of-the-art image registration methods.

Some key features of the framework:

  • automatic execution of image registration of a sequence of image pairs
  • integrated evaluation of registration performances using Target Registration Error (TRE)
  • integrated visualization of performed registration
  • running several image registration experiment in parallel
  • resuming unfinished sequence of registration benchmark
  • handling around dataset and creating own experiments
  • rerun evaluation and visualisation for finished experiments
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Description

It is an interactive front-end visualization for registration software based on Elasix (VTK/ITK)

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