The team at MARS Bioimaging developed the MARS Imaging System for quantitative colour imaging for use in research and medicine.
The MARS Imaging System incorporates 15 years of research and development into spectral photon-counting CT, several patents and MARS owned IP, and the Medipix detector developed at CERN. The two main principles underpinning the MARS Imaging System are detection and analysis.
Detection, or gathering spectral data, can be thought of as the ‘easy’ step, while analysing and utilising that data is the ‘hard’ step. The MARS team have produced advanced, patented software for processing spectral x-ray data. Scroll down to learn more about these topics.
Detection is an integral element of any imaging system
The Medipix detector chip has been in development since the 1970s. First used for particle experiments at the Euopean Organisation for Nuclear Research (CERN), it quickly became apparent that this technology could be applied to medical x-ray imaging.
The Medipix uses very small pixels and a very clever scheme to correctly measure the energy and position of each x-ray photon, which provides much higher spatial and energy resolution compared to standard clinical CT systems.
Using the MARS Imaging System, you will collect 10x more information than standard CT, and produce up to eight different material maps. Our system is energy resolving, rather than energy-integrating.
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Material phantoms, when are they important?
Quantitative colour imaging in research using the MARS Imaging System relies on a material or calibration phantom to accurately determine each material of interest.
If you use iodine, gold, hafnium, or even all of the above, you can easily program the MARS Imaging System, using a material phantom, to identify up to eight different materials in a single exposure.
To learn more about this topic, click here.
Advanced algorithms create quantitative colour images in the lab and in the clinic
Our powerful imaging chain consists of two steps. Step one is an iterative algebraic reconstruction algorithm. Step two is material decomposition algorithm that produces material maps from energy resolved attenuation data.
Using the MARS Imaging System, you can create quantitative colour images in the lab and in the clinic.
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Machine learning in photon-counting CT
We are always looking to improve the speed and quality of our material analysis as we understand these aspects are critical for SPCCT to become routinely used in the clinic.
One of the many tools we are working with is machine learning.
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