Technique developed for higher accuracy super-resolution microscopy

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A team from the University of Texas at Dallas led by Professor Raimund Ober has discovered a method to almost eliminate image-deteriorating factors in super-resolution localisation microscopy techniques.

Super-resolution localisation microscopy can capture images of sub-cellular structures with a higher resolution than the diffraction limit, approximately 250nm. However, the technique is typically limited in positional accuracy by the pixelation and noise generated by CCD and EMCCD detectors.

The scientists at the University of Texas at Dallas developed a new technique called Ultrahigh Accuracy Imaging Modality (UAIM) that improves parameter estimation accuracy by more than 200 per cent. The work published in Nature Methods used an Andor iXon3 897 EMCCD camera.

‘UAIM uses the EMCCD camera to its fullest potential, beyond what is commonly believed to be possible by the scientific imaging community,’ said Ober. ‘Specifically, our results show that when an average of less than one photon is detected per pixel, the excess noise due to the camera's electron multiplication process is reduced to such an extent that an accuracy can be obtained that approaches the absolute best accuracy attainable only with an imaging detector that neither pixelates nor adds measurement noise to the image data.’

Colin Coates of Andor commented: ‘UAIM uses the iXon3 EMCCD detector at a high level of signal amplification and in a highly unconventional and counterintuitive setting in which the number of photons detected in each pixel of an acquired image averages less than one. The resulting image does not give a visually clear representation of the object of interest as might be expected for obtaining high localisation accuracies but, significantly, this new imaging method is applicable to all types of estimation problems. Although Professor Ober and his team demonstrated UAIM using single molecule localisation, it can be applied equally to other EMCCD imaging applications, for example in astronomy, surveillance and machine vision.’

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