NEWS FROM PHOTONICS WEST


Lens-free microscope promises to speed medical diagnostics


CEA-Leti presented its computational microscope at Photonics West


T


he French institute CEA-Leti has built a microscope without an objective lens that is able to screen 10,000 cells


in real-time at several frames per second. Te new lens-free technology, which was


shown at CES and SPIE Photonics West in San Francisco, opens up fast, automated cell screening in point-of-care applications, such as meningitis diagnosis. Other uses include complete blood


counts, blood coagulation tests, monitoring bioreactors for developing pharmaceuticals and other drug screening processes. Lens free, which dispenses with the


objective lens of a microscope and instead reconstructs an image digitally using a holographic pattern and an algorithm, is a reasonably mature technology. CEA-Leti has been working on lens free for 10 years, has 25 patents registered, and in 2016 commercialised it through the company Iprasense, which sells live cell imaging and counting systems based on the technology. Now, CEA-Leti researchers have sped


up image reconstruction and data analysis using deep learning, which makes it able to identify, count and track different cell types in real time. It’s this new technology that was presented at Photonics West, in a workshop organised by the institute on 5 February,


‘For this technology to be accepted, you need to have results right away’


and in conference sessions on 3 February at Photonics West’s sister show, Bios. Dr Cédric Allier, project manager at


CEA-Leti, who spoke on computational microscopy during the workshop, told Imaging and Machine Vision Europe that it used to take 30 minutes to reconstruct one image, such was the complexity of the algorithm. Now, using deep learning, an image can be reconstructed in one second. ‘For this technology to be accepted in the field of [medical] diagnostics, you need to have the results right away,’ he said. Te lens-free technology is 10 times less


expensive than an optical microscope and can cover a large field of view of 30mm2, or 10,000 cells per image. It is able to detect bacteria at a resolution down to 1µm. It works by shining near-infrared light on


Imaging wins big at Photonics West The Prism Awards reflect


Three imaging firms have won Prism Awards at SPIE’s flagship event, Photonics West, in San Francisco. Israeli firm Inspekto won in the manufacturing category for its quality assurance system; Outsight for its 3D semantic camera in the transportation category; and WaveOptics for waveguides for augmented reality, in vision technology.


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developments taking place across photonics. SPIE received 105 applications from 18 countries, and finalists and winners were selected by a panel of judges from the technology commercialisation and funding sectors. Inspekto’s S70 system is designed to cut the integration cost of industrial inspection


a biological sample. Te light is diffracted by the cells and interference between the diffracted light and incident light wave creates a holographic pattern, which is captured by a CMOS sensor. Te image is then reconstructed digitally. In collaboration with Marseille-


Méditerranée University Medical Centre, the group conducted a study comparing its lens-free microscope with a standard cerebrospinal fluid cytology test for diagnosing meningitis. Te work, published in Scientific Reports, found the lens-free microscopy algorithm, adapted for counting cerebrospinal fluid cells and discriminating between leukocytes and erythrocytes, yielded 100 per cent sensitivity and 79 per cent specificity. It compares to confirmed diagnostics in a blind lens-free analysis of 116 cerebrospinal fluid specimens. Allier said deep learning has overcome


the bottleneck the technology faced about the speed of image reconstruction and cell analysis. ‘To identify, count and track cells with software remains challenging,’ he said. ‘We can address this with deep learning; it’s faster and more precise.’ Cell cultures, for example, can cover 400


different cell lines, each of which would almost require a dedicated algorithm using traditional image processing techniques, said Allier. Tere are also different cell culture conditions, which complicates image analysis. All of this, he feels, can be overcome with deep learning. Allier added the next step for CEA-Leti is to commercialise this updated technology. O


equipment thanks to its AI- based learning approach to machine vision. Outsight’s 3D semantic


camera combines lidar ranging with spectral analysis that can identify the chemical composition of objects. The company is working with OEMs and tier one suppliers in the automotive, aeronautics and surveillance markets. The


camera also has simultaneous localisation and mapping capability on the chip. WaveOptics makes


waveguides for AR smart glasses. The technology directs light into the user’s eye, so a digital image can be overlaid onto the real world. The Prism Award winners were announced on 5 February at Photonics West.


FEBRUARY/MARCH 2020 IMAGING AND MACHINE VISION EUROPE 15


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