Real-time Dynamic Range Research Articles

Real-time dynamic range and signal to noise enhancement in beam-scanning microscopy by integration of sensor characteristics, data acquisition hardware, and statistical methods.

Despite the ubiquitous use of multi-photon and confocal microscopy measurements in biology, the core techniques typically suffer from fundamental compromises between signal to noise (S/N) and linear dynamic range (LDR). In this study, direct synchronous digitization of voltage transients coupled with statistical analysis is shown to allow S/N approaching the theoretical maximum throughout an LDR spanning more than 8 decades, limited only by the dark counts of the detector on the low end and by the intrinsic nonlinearities of the photomultiplier tube (PMT) detector on the high end. Synchronous digitization of each voltage transient represents a fundamental departure from established methods in confocal/multi-photon imaging, which are currently based on either photon counting or signal averaging. High information-density data acquisition (up to 3.2 GB/s of raw data) enables the smooth transition between the two modalities on a pixel-by-pixel basis and the ultimate writing of much smaller files (few kB/s). Modeling of the PMT response allows extraction of key sensor parameters from the histogram of voltage peak-heights. Applications in second harmonic generation (SHG) microscopy are described demonstrating S/N approaching the shot-noise limit of the detector over large dynamic ranges.

Evaluation of the Abbott Investigational Use Only RealTi m e Hepatitis C Virus (HCV) Assay and Comparison to the Roche TaqMan HCV Analyte-Specific Reagent Assay

The accurate and sensitive measurement of hepatitis C virus (HCV) RNA is essential for the clinical management and treatment of infected patients and as a research tool for studying the biology of HCV infection. We evaluated the linearity, reproducibility, precision, limit of detection, and concordance of viral genotype quantitation of the Abbott investigational use only RealTime HCV (RealTime) assay using the Abbott m2000 platform and compared the results to those of the Roche TaqMan Analyte-Specific Reagent (TaqMan) and Bayer Versant HCV bDNA 3.0 assay. Comparison of 216 samples analyzed by RealTime and TaqMan assays produced the following Deming regression equation: RealTime = 0.940 (TaqMan) + 0.175 log(10) HCV RNA IU/ml. The average difference between the assays was 0.143 log(10) RNA IU/ml and was consistent across RealTime's dynamic range of nearly 7 log(10) HCV RNA IU/ml. There was no significant difference between genotypes among these samples. The limit of detection using eight replicates of the World Health Organization HCV standard was determined to be 7.74 HCV RNA IU/ml by probit analysis. Replicate measurements of commercial genotype panels were significantly higher than TaqMan measurements for most samples and showed that the RealTime assay is able to detect all genotypes with no bias. Additionally, we showed that the amplicon generated by the widely used Roche COBAS Amplicor Hepatitis C Virus Test, version 2.0, can act as a template in the RealTime assay, but potential cross-contamination could be mitigated by treatment with uracil-N-glycosylase. In conclusion, the RealTime assay accurately measured HCV viral loads over a broad dynamic range, with no significant genotype bias.

Real-time image dynamic range compensation for an optical imaging system

This paper presents the development and implementation of a real-time dynamic range compensation system for optical images. Compared with conventional automatic brightness contrast compensators that are based on the average image or pixel intensity level, the proposed system utilizes histogram-profiling techniques to continuously compensate for the dynamic range of the processed video signal. The algorithms are implemented in real time with a frame grabber card forming the front-end video capture element. The proposed technique yields better image compensation compared with conventional methods. Various methods are used in order for the analysis to be statistically valid.

A real-time image dynamic range compensation for scanning electron microscope imaging system

This paper presents the development and implementation of a real-time dynamic range compensation system for scanning electron microscope (SEM) imaging applications. Compared with conventional automatic brightness contrast compensators that are based on the average image or pixel intensity level, the proposed system utilizes histogram-profiling techniques to compensate continuously the dynamic range of the processed video signal. The algorithms are implemented in software with a frame grabber card forming the front-end video capture element. The proposed technique yields better image compensation compared with conventional methods.