Hyperspectral Imaging
Hyperspectral imaging is a technique combining spectroscopy and imaging, where each image is acquired at a narrow band of the electromagnetic spectrum. As an example, the human eye sees the light in three bands (red, green and blue) of the visible spectrum. At the same time, hyperspectral imaging divides the spectrum in more bands, typically covering the visible and near-infrared range.
The term hyperspectral imaging refers to the continuous acquisition of narrow bands (< 10 nm) across the electromagnetic spectrum. With our unique technology we are able to obtain bands of 2nm-4nm wide and even 0.3nm. On the contrary, multi-spectral imaging covers only a discrete number of bands, and is often performed with a filter wheel.
Through the analysis of the spectral and spatial information contained in each pixel of the image, it is possible to identify unique spectral signatures and assign them to the components of the sample under investigation. For example, the material or tissue analysand can be mapped according to its molecular components.
Hyperspectral Data Cube
The monochromatic images acquired form what we call a hyperspectral data cube, which contains both the spatial and spectral information of a sample, forming a 3-dimensional (3D) cube.
In the hyperspectral cube, the first two dimensions are spatial (x, y-axis), while the third dimension (z-axis) is the wavelength. Depending on the size of the sensor used, one single cube can represent many gigabytes of data representing an extremely rich source of information for material scientists or biomedical researchers.
Applications
Lifescience
IN VIVO NIR-II IMAGING: A DISRUPTIVE FORCE FOR PRECLINICAL RESEARCH
Hyperspectral imaging has opened up many doors across research fields and industries; in vivo imaging in the second biological window using NIR-II is one of the most recent discoveries that holds endless potentials in opening up new windows in the life science research.
Preclinical optical imaging suffers from the inability to localise signals due to complications associated with light absorption, scattering and auto-fluorescence in living tissues. In vivo optical imaging can localise a signal well when it is at the surface but not when it is deep in the organism.
Preclinical biologists still strongly desire the ability to rapidly localise optical signals in vivo, but their discussions with imaging physicists often end up in a standstill. Biologists ask: can I use optical imaging to see my mCherry cancer cells in vivo? What about my luciferase cells? The answer is: it depends on many different factors such as the temperature of the animal, the optical properties of organs, how deep they are and how many photons come out.
NIR-II in vivo imaging is not impacted in the same way by drawbacks of light propagation in living tissues, thus enabling real-time imaging of optical probes much deeper in the organism and with much higher resolutions.
One of the breakthroughs in the field of in vivo SWIR imaging has been the demonstration that both NIR-I and NIR-II probes can work well for this application. There is an abundance of probes for the new imaging modality and many of them remain to be validated. he ball is back in the court for biologists to take. No longer will biologists need to accept the “oh well, I guess it depends” answer when asking an optical imaging physicist if it is possible to localise their probes in vivo.
MATERIAL SCIENCE
IN VIVO NIR-II IMAGING: A DISRUPTIVE FORCE FOR PRECLINICAL RESEARCH
Semiconductor materials are present in a vast collection of devices, ranging from transistors to solar cells, multiprocessors to light emitting diodes. In order to improve further the next generation of such devices, researchers need to study the fundamental properties of semiconductor materials and perform quality control measurements. To do so, accurate characterisation systems and methods are paramount, and hyperspectral imagers possess the essential modalities to perform these tasks through the rapid collection of highly valuable spatial and spectral data.
The intrinsic specificity of Raman scattering confers to this imaging platform the ability to measure the uniformity and morphology of a wide variety of materials. It also allows a fast identification of the composition and stoichiometry, while providing spatial distribution of stresses and constraints. This platform was successfully used to characterise various properties of chalcogenide glasses, GaAs and GeSn/Ge/Si thin films, the identification of MoS2 layers, and the analysis of constraints in a Si wafer covered by SiO2.
Photoluminescence and electroluminescence are also widely used characterisation technique, providing a fast spatial distribution of key properties of semiconductors samples. It was successfully employed to characterise different defects present in SiC pin diodes and to study the uniformity of optoelectronic properties in CIGS, CIS and GaAs solar cells.
To understand more about the types of hyperspectral imaging systems we provide, click here.
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