Reduction of Quantum Noise in Transmittance Estimation Using PhotoneCorrelated Beams

The accuracy of optical measurements at low light levels is limited by the quantum noise of the source and by the random nature of the interaction with the measured object. The source noise may be reduced by use of nonclassical photon-number squeezed light. This paper considers the use of two photon-correlated beams (generated, for example, by spontaneous parametric downconversion) to measure the optical transmittance of an object. The photons of each beam obey a random Poisson process, but are synchronized in time. One beam is used to probe the object while the other is used as a reference providing information on the realization of the random arrival of photons at the object. The additional information available by such measurement may be exploited to improve the accuracy of the measurement. Various estimators, including the maximum likelihood estimator, are considered and their performance is evaluated and compared with the measurement based on single-beam conventional (Poisson) source and maximally squeezed (fixed photon number) source. The performance advantage established in this paper depends on parameters such as the intensity of the source, the transmittance of the object, the quantum efficiency of the detectors, the background noise, and the degree of correlation of the photon numbers in the two beams

Maximum-likelihood image estimation using photon-correlated beams

A theory is presented addressing the fundamental limits of image estimation in a setup that uses two photon-correlated beams. These beams have the property that their photon arrivals, as a point process, are ideally synchronized in time and space. The true image represents the spatial distribution of the optical transmittance (or reflectance) of an object. In this setup, one beam is used to probe the image while the other is used as a reference providing additional information on the actual number of photons impinging on the object. This additional information is exploited to reduce the effect of quantum noise associated with the uncertainty in the number of photons per pixel. A stochastic model for the joint statistics of the two observation matrices is developed and used to obtain a local maximum-likelihood estimator of the image. The model captures the nonideal nature of the correlation between the photons of the beams by means of a simple random translation model. The mean-square error of the estimator is evaluated and compared to the corresponding conventional techniques. Conditions for the performance advantage of the proposed estimator are examined in terms of key system parameters. The theoretical predictions are demonstrated by means of simulation

Effect of denoising on the quality of reconstructed images in digital breast tomosynthesis

Individual projection images in Digital Breast Tomosynthesis (DBT) must be acquired with low levels of radiation,\ud which significantly increases image noise. This work investigates the influence of a denoising algorithm and the\ud Anscombe transformation on the reduction of quantum noise in DBT images. The Anscombe transformation is a\ud variance-stabilizing transformation that converts the signal-dependent quantum noise to an approximately signalindependent\ud Gaussian additive noise. Thus, this transformation allows for the use of conventional denoising algorithms,\ud designed for additive Gaussian noise, on the reduction of quantum noise, by working on the image in the Anscombe\ud domain. In this work, denoising was performed by an adaptive Wiener filter, previously developed for 2D\ud mammography, which was applied to a set of synthetic DBT images generated using a 3D anthropomorphic software\ud breast phantom. Ideal images without noise were also generated in order to provide a ground-truth reference. Denoising\ud was applied separately to DBT projections and to the reconstructed slices. The relative improvement in image quality\ud was assessed using objective image quality metrics, such as peak signal-to-noise ratio (PSNR) and mean structural\ud similarity index (SSIM). Results suggest that denoising works better for tomosynthesis when using the Anscombe\ud transformation and when denoising was applied to each projection image before reconstruction; in this case, an average\ud increase of 9.1 dB in PSNR and 58.3% in SSIM measurements was observed. No significant improvement was observed\ud by using the Anscombe transformation when denoising was applied to reconstructed images, suggesting that the\ud reconstruction algorithm modifies the noise properties of the DBT images.FAPESPCNP

Restauration des images en scintigraphie planaire et SPECT suite à la réduction des doses administrées et des temps de pause

This work consists in decreasing the administered dose in planar imaging to reduce patient exposure and acquisition time to avoid motion artifacts. This has been addressed by developing appropriate treatment approaches for conservation or even improved diagnostic quality images. We have led to a method of restoring which proves the most appropriate for the maximum recovery of diagnostic images detail. We realized our acquisitions in vitro on phantoms that we designed to simulate the main event of variability in activity seen on clinical cases as well as on standard phantoms.Ce travail consiste à réduire la dose administrée en scintigraphie planaire afin de réduire l'exposition des patients et à réduire le temps d'acquisition pour éviter les artéfacts de mouvement. Ceci a été abordé en élaborant des approches de traitement adéquates permettant la conservation ou même l'amélioration des qualités diagnostiques des images. Nous avons aboutit à une méthode de restauration qui s'avère la plus adéquate pour la récupération de maximum de détails de diagnostics des images. Nous avons réalisé nos acquisitions in-vitro sur des fantômes que nous avons conçus de manière à simuler les principaux cas de variabilité de l'activité remarquée sur des cas cliniques ainsi que sur des fantômes standards