• The new company offers innovative industrial inspection solutions combining X-ray detection and artificial intelligence
• The first applications of the technology focus on the food security sector
• The spin-off was created in the framework of the Mobile World Capital’s The Collider (MWC) programme
On November 3, 2020, the Institute for High Energy Physics (IFAE), a BIST centre, became a partner of the company Deep Detection SL and the technology transfer from IFAE to the new spin-off became effective. Deep Detection is comprised of a scientific team made up of IFAE researchers Dr. Mokhtar Chmeissani and Dr. José Gabriel Macías, and a business team headed by David Ciudad (CEO). The company aims to offer detection solutions to the industry thanks to a multispectral X-ray camera that includes photon-counting technology capable of detecting previously undetectable foreign bodies, such as plastics, wood, or bones.
Deep Detection is based on a technology developed at IFAE in the Medical Imaging group led by Dr. Mokhtar Chmeissani with the aim of creating medical and industrial applications derived from the knowledge obtained at IFAE in the development of detectors for particle physics experiments.
The developed system is made of chips specially designed to perform x-ray quality control tests integrated in a spectral camera for in-line scanning. The technology was developed within the framework of the Retos Colaboración (ERICA) project of the MICINN and an AGAUR “Producte” grant (LINDA). The chip was assembled entirely in IFAE’s microelectronics laboratory.
“With the existing technology so far, we could either get a low-resolution x-ray image with good spectral information, or a high-resolution x-ray image with very little spectral information. At IFAE we have solved this problem. The technology we have developed allows us to use X-ray detectors with small pixels to achieve a good spatial resolution, and generate, at the same time, images with different energy levels”, explains Mokhtar Chmeissani.
“The spectral cameras we have developed allow us to obtain images of excellent quality, in multiple channels, of objects passing at 60 meters per second through a production line. The cameras can count up to 10 million photons per mm² every second and this allows us to obtain, in each channel, the image quality needed to discriminate and identify materials of very similar densities such as plastics in yoghurts with fruit or cereals or uncalcified bones in filleted chicken, two of today’s most complex food security challenges”, adds José Gabriel Macias.
The technology was submitted to the acceleration programme The Collider (MWC) and was among the 15 selected for the validation phase of the business opportunity, competing with more than 200 projects throughout Spain. It was finally chosen as one of five business projects for the venture building phase, with the consequent creation of the company Deep Detection SL on July 13, 2020, with an initial investment of € 50,000 from the MWC foundation, a partner in the company.
Applications in the food industry
X-ray inspection is used in the food and beverage industry to carry out quality controls and ensure safety, specifically in the detection of foreign bodies such as metals, glass, wood, etc. All materials that have high densities are likely to be detected with current technology, but not when it comes to low density materials.
“The big challenge of X-ray inspection in the industry is the detection of plastics, and we can provide a solution for it. In fact any low density element is an industrial challenge and a current problem. Plastics in yoghurts, bones or the amount of fat in meat … they are problems that we can solve”, says David City, CEO of Deep Detection.
The key to this technology lies in the combination of X-ray imaging and artificial intelligence. The benefits of artificial intelligence or deep learning can only be obtained if the quality of the captured data is high enough for the algorithms to differentiate key patterns. Conventional X-ray detectors cannot handle complex detection problems because the images they generate are too noisy. The team at IFAE has developed a solution from scratch to capture high-definition X-ray data, meaning Deep Detection can apply the latest artificial intelligence strategies to improve the quality and safety of manufactured products.
More information: www.deepdetection.tech