Mr. Eiji Toda Profile

Eiji Toda

at Hamamatsu Photonics KK

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Proceedings Article | 13 February 2012 Paper

Optimization of precision localization microscopy using CMOS camera technology

Stephanie Fullerton, Keith Bennett, Eiji Toda, Teruo Takahashi

Proceedings Volume 8228, 82280T (2012) https://doi.org/10.1117/12.906336

KEYWORDS: Cameras, Microscopy, Quantum efficiency, Signal to noise ratio, Molecules, Interference (communication), Sensors, CMOS technology, Device simulation, CCD cameras

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Light microscopy imaging is being transformed by the application of computational methods that permit the detection of spatial features below the optical diffraction limit. Successful localization microscopy (STORM, dSTORM, PALM, PhILM, etc.) relies on the precise position detection of fluorescence emitted by single molecules using highly sensitive cameras with rapid acquisition speeds. Electron multiplying CCD (EM-CCD) cameras are the current standard detector for these applications. Here, we challenge the notion that EM-CCD cameras are the best choice for precision localization microscopy and demonstrate, through simulated and experimental data, that certain CMOS detector technology achieves better localization precision of single molecule fluorophores. It is well-established that localization precision is limited by system noise. Our findings show that the two overlooked noise sources relevant for precision localization microscopy are the shot noise of the background light in the sample and the excess noise from electron multiplication in EM-CCD cameras. At low light conditions (< 200 photons/fluorophore) with no optical background, EM-CCD cameras are the preferred detector. However, in practical applications, optical background noise is significant, creating conditions where CMOS performs better than EM-CCD. Furthermore, the excess noise of EM-CCD is equivalent to reducing the information content of each photon detected which, in localization microscopy, reduces the precision of the localization. Thus, new CMOS technology with 100fps, <1.3 e^- read noise and high QE is the best detector choice for super resolution precision localization microscopy.

Proceedings Article | 13 February 2012 Paper

Camera simulation engine enables efficient system optimization for super-resolution imaging

Stephanie Fullerton, Keith Bennett, Eiji Toda, Teruo Takahashi

Proceedings Volume 8228, 822811 (2012) https://doi.org/10.1117/12.906346

KEYWORDS: Cameras, Device simulation, Imaging systems, Microscopy, Interference (communication), Super resolution, Quantum efficiency, Molecules, Image processing, Photonics

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Quantitative fluorescent imaging requires optimization of the complete optical system, from the sample to the detector. Such considerations are especially true for precision localization microscopy such as PALM and (d)STORM where the precision of the result is limited by the noise in both the optical and detection systems. Here, we present a Camera Simulation Engine (CSE) that allows comparison of imaging results from CCD, CMOS and EM-CCD cameras under various sample conditions and can accurately validate the quality of precision localization algorithms and camera performance. To achieve these results, the CSE incorporates the following parameters: 1) Sample conditions including optical intensity, wavelength, optical signal shot noise, and optical background shot noise; 2) Camera specifications including QE, pixel size, dark current, read noise, EM-CCD excess noise; 3) Camera operating conditions such as exposure, binning and gain. A key feature of the CSE is that, from a single image (either real or simulated "ideal") we generate a stack of statistically realistic images. We have used the CSE to validate experimental data showing that certain current scientific CMOS technology outperforms EM-CCD in most super-resolution scenarios. Our results support using the CSE to efficiently and methodically select cameras for quantitative imaging applications. Furthermore, the CSE can be used to robustly compare and evaluate new algorithms for data analysis and image reconstruction. These uses of the CSE are particularly relevant to super-resolution precision localization microscopy and provide a faster, simpler and more cost effective means of system optimization, especially camera selection.

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