Probabilistic modeling for single-photon lidar

Lidar is an increasingly prevalent technology for depth sensing, with applications including scientific measurement and autonomous navigation systems. While conventional systems require hundreds or thousands of photon detections per pixel to form accurate depth and reflectivity images, recent results for single-photon lidar (SPL) systems using single-photon avalanche diode (SPAD) detectors have shown accurate images formed from as little as one photon detection per pixel, even when half of those detections are due to uninformative ambient light. The keys to such photon-efficient image formation are two-fold: (i) a precise model of the probability distribution of photon detection times, and (ii) prior beliefs about the structure of natural scenes. Reducing the number of photons needed for accurate image formation enables faster, farther, and safer acquisition. Still, such photon-efficient systems are often limited to laboratory conditions more favorable than the real-world settings in which they would be deployed. This thesis focuses on expanding the photon detection time models to address challenging imaging scenarios and the effects of non-ideal acquisition equipment. The processing derived from these enhanced models, sometimes modified jointly with the acquisition hardware, surpasses the performance of state-of-the-art photon counting systems. We first address the problem of high levels of ambient light, which causes traditional depth and reflectivity estimators to fail. We achieve robustness to strong ambient light through a rigorously derived window-based censoring method that separates signal and background light detections. Spatial correlations both within and between depth and reflectivity images are encoded in superpixel constructions, which fill in holes caused by the censoring. Accurate depth and reflectivity images can then be formed with an average of 2 signal photons and 50 background photons per pixel, outperforming methods previously demonstrated at a signal-to-background ratio of 1. We next approach the problem of coarse temporal resolution for photon detection time measurements, which limits the precision of depth estimates. To achieve sub-bin depth precision, we propose a subtractively-dithered lidar implementation, which uses changing synchronization delays to shift the time-quantization bin edges. We examine the generic noise model resulting from dithering Gaussian-distributed signals and introduce a generalized Gaussian approximation to the noise distribution and simple order statistics-based depth estimators that take advantage of this model. Additional analysis of the generalized Gaussian approximation yields rules of thumb for determining when and how to apply dither to quantized measurements. We implement a dithered SPL system and propose a modification for non-Gaussian pulse shapes that outperforms the Gaussian assumption in practical experiments. The resulting dithered-lidar architecture could be used to design SPAD array detectors that can form precise depth estimates despite relaxed temporal quantization constraints. Finally, SPAD dead time effects have been considered a major limitation for fast data acquisition in SPL, since a commonly adopted approach for dead time mitigation is to operate in the low-flux regime where dead time effects can be ignored. We show that the empirical distribution of detection times converges to the stationary distribution of a Markov chain and demonstrate improvements in depth estimation and histogram correction using our Markov chain model. An example simulation shows that correctly compensating for dead times in a high-flux measurement can yield a 20-times speed up of data acquisition. The resulting accuracy at high photon flux could enable real-time applications such as autonomous navigation

Computational Imaging with Limited Photon Budget

The capability of retrieving the image/signal of interest from extremely low photon flux is attractive in scientific, industrial, and medical imaging applications. Conventional imaging modalities and reconstruction algorithms rely on hundreds to thousands of photons per pixel (or per measurement) to ensure enough signal-to-noise (SNR) ratio for extracting the image/signal of interest. Unfortunately, the potential of radiation or photon damage prohibits high SNR measurements in dose-sensitive diagnosis scenarios. In addition, imaging systems utilizing inherently weak signals as contrast mechanism, such as X-ray scattering-based tomography, or attosecond pulse retrieval from the streaking trace, entail prolonged integration time to acquire hundreds of photons, thus rendering high SNR measurement impractical. This dissertation addresses the problem of imaging from limited photon budget when high SNR measurements are either prohibitive or impractical. A statistical image reconstruction framework based on the knowledge of the image-formation process and the noise model of the measurement system has been constructed and successfully demonstrated on two imaging platforms – photon-counting X-ray imaging, and attosecond pulse retrieval. For photon-counting X-ray imaging, the statistical image reconstruction framework achieves high-fidelity X-ray projection and tomographic image reconstruction from as low as 16 photons per pixel on average. The capability of our framework in modeling the reconstruction error opens the opportunity of designing the optimal strategies to distribute a fixed photon budget for region-of-interest (ROI) reconstruction, paving the way for radiation dose management in an imaging-specific task. For attosecond pulse retrieval, a learning-based framework has been incorporated into the statistical image reconstruction to retrieve the attosecond pulses from the noisy streaking traces. Quantitative study on the required signal-to-noise ratio for satisfactory pulse retrieval enabled by our framework provides a guideline to future attosecond streaking experiments. In addition, resolving the ambiguities in the streaking process due to the carrier envelop phase has also been demonstrated with our statistical reconstruction framework

APPLICATIONS OF POINT PROCESS MODELS TO IMAGING AND BIOLOGY

This dissertation deals with point process models and their applications to imaging and messenger RNA (mRNA) transcription. We address three problems. The first problem arises in two-photon laser scanning microscopy. We model the process by which photons are counted by a detector which suffers from a dead period upon registration of a photon. In this model, we assume that there are a Poisson (α) number of excited molecules, with exponentially distributed waiting times for the emissions of photons. We derive the exact distribution of all observed counts, rather than grouped counts which were used earlier. We use it to get improved estimates of the Poisson intensity, which leads to images with higher signal-to-noise ratio. This improvement is because grouping of count data results in loss of information. We illustrate this improvement on imaging data of paper fibers. Next, we study two variants of this model: the first uses a finite time horizon and the second considers gamma waiting times for the emissions. The second problem concerns the Conway-Maxwell-Poisson distribution for count data. This family has been proposed as a generalization of the Poisson for handling overdispersion and underdisperson. Because the normalizing constant of this family is hard to compute, good approximations for it are needed. We provide a statistical approach to derive an existing approximation more simply. However, this approximation does not perform well across all the parameter ranges. Therefore, we introduce correction terms to improve its performance. For other parts of the parameter space, we use the geometric and Bernoulli distributions, with correction terms based on Taylor expansions. Using numerical examples, we show that our approximations are much better than earlier proposed methods. In the last problem, we present a new application for Conway-Maxwell-Poisson family. We use the generalized linear model setting of this family to study mRNA counts. We then compare its performance with the existing methods used for modeling mRNAs, such as the negative binomial. This empirical model can be a good modeling tool for dispersed mRNA count data when a biophysically based model is not available

Surface Plasmon Induced Luminescence as a Tool for Study of the Ageing of Polymeric Materials.

Lo scopo della presente tesi, svolta presso il Laboratorio LAPLACE di Tolosa, è quello di indagare sulle proprietà ottiche di campioni composti da un substrato di materiale polimerico (bi-axially oriented polyprophilene, BOPP) ricoperto con diversi tipi di elettrodi principalmente tramite misure di elettroluminescenza e di comprendere come queste siano legate al suo deterioramento e invecchiamento Nella prima parte della tesi, verranno illustrate le misure effettuate su due diverse strutture MIM (metal-insulator-metal), la prima ottenuta utilizzando oro e la seconda utilizzando ITO come elettrodi. Nella seconda parte, invece, le misure sono state effettuate su campioni multistrato contenenti nano compositi a base di argento, ricoperte con uno strato di ITO che fungerà da elettrodo. Le misure sulla prima tipologia di campioni hanno evidenziato la presenza di due componenti principali nelle emissioni dovute a elettroluminescenza, una prodotta dal materiale bulk (BOPP) e una scaturita dall’interazione tra il substrato e l’elettrodo metallico, grazie al coinvolgimento dei plasmoni di superficie. Lo scopo della seconda parte della tesi è quello di comprendere l’effetto che le particelle di argento potrebbero avere sui plasmoni superficiali e sulle emissioni luminose dovute a elettroluminescenza. I risultati ottenuti su questi campioni hanno evidenziato un livello di luce prodotto da elettroluminescenza incredibilmente maggiore rispetto ai campioni aventi ITO e oro come elettrodi. In conclusione l’impatto delle nano particelle di argento sulle emissioni per elettroluminescenza da BOPP possono essere molteplici e saranno necessari ulteriori studi per comprendere in modo dettagliato tale meccanismo. L’effetto mostrato qui potrebbe risultare molto utile per capire meglio l’elettroluminescenza nei materiali polimerici isolanti da un lato e dall’altro le proprietà foto-fisiche delle nanoparticelle metalliche

Reliability and accuracy of single-molecule FRET studies for characterization of structural dynamics and distances in proteins

Single-molecule Förster-resonance energy transfer (smFRET) experiments allow the study of biomolecular structure and dynamics in vitro and in vivo. We performed an international blind study involving 19 laboratories to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems with distinct conformational changes and dynamics, we obtained an uncertainty of the FRET efficiency ≤0.06, corresponding to an interdye distance precision of ≤2 Å and accuracy of ≤5 Å. We further discuss the limits for detecting fluctuations in this distance range and how to identify dye perturbations. Our work demonstrates the ability of smFRET experiments to simultaneously measure distances and avoid the averaging of conformational dynamics for realistic protein systems, highlighting its importance in the expanding toolbox of integrative structural biology

Reliability and accuracy of single-molecule FRET studies for characterization of structural dynamics and distances in proteins

Single-molecule Förster-resonance energy transfer (smFRET) experiments allow the study of biomolecular structure and dynamics in vitro and in vivo. We performed an international blind study involving 19 laboratories to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems with distinct conformational changes and dynamics, we obtained an uncertainty of the FRET efficiency ≤0.06, corresponding to an interdye distance precision of ≤2 Å and accuracy of ≤5 Å. We further discuss the limits for detecting fluctuations in this distance range and how to identify dye perturbations. Our work demonstrates the ability of smFRET experiments to simultaneously measure distances and avoid the averaging of conformational dynamics for realistic protein systems, highlighting its importance in the expanding toolbox of integrative structural biology

Une approche du vieillissement électrique des isolants polymères par mesure d'électroluminescence et de cathodoluminescence

Electroluminescence (EL) of insulating polymers is a subject of great interest because it is associated with electrical ageing and could provide the signature of excited species under electric field. Electrical ageing and breakdown in insulating polymers is of fundamental interest to the researchers, the design engineers, the manufacturers and the customers of electrical apparatus. In this respect, Partial Discharge (PD) is a harmful process leading to ageing and failure of insulating polymers. However, with the development of the materials and apparatus, PDs can be weakened or avoided in some situations, e.g. extra high voltage cables, capacitors, etc. Therefore, there is urgent demand for understanding electrical degradation mechanisms under high electric field, which can be triggered by energetic charge carriers. In this work, Electroluminescence, EL, and cathodoluminescence, CL, excited under electron beam, along with other luminescence-family techniques are carried out for probing polyolefins and other insulating polymers. In order to uncover the excitons formation in Polypropylene (PP) and Polyethylene (PE) thin films, the field dependence of EL and current under DC stress and field dependence of EL and phase-resolved EL under AC stress, are investigated. The EL spectra of both PP and PE have the same main peak at approximately 570 nm, pointing towards similar chemical structures and defects in both polyolefins, and same route to degradation. This main peak can be complemented by an emission at approximately 750 nm dominating at low field. Electrode effect on the EL of Polyethylene Naphthalte (PEN) was investigated to understand the origin of the red emission at 750 nm. Through field dependence of EL and phase-resolved EL of Au or ITO electrodes, we proved the red component is due to the nature of electrode, more precisely Surface Plasmons and/or interface states. Further thorough study was carried out on cathodoluminescence of insulating polymers. Thin films of PP, PE, along with Polyethylene Naphthalate (PEN) and Polyether Ether Ketone (PEEK) were irradiated under electron beam up to 5 keV to be excited. We could reconstruct EL and CL spectra of both PE and PP using four elementary components: i.e. Fluorescence, Chemiluminescence, Recombination-induced Luminescence, and main component of the EL spectrum at 570 nm reported above and constituting an ageing marker. For the first time the nature of both EL and CL in polyolefins is uncovered, containing four basic components with different relative contributions. Identification of these spectral components is helpful to interpret the nature of light emission from polyolefins and other insulating polymers and to bridge the gap between space charge distribution and electrical ageing or breakdown. Through researches on EL and CL in several insulating polymers, i.e. polyolefins and a polyester, excitons formation and relaxation processes under electric stress and kinetic electrons are evidenced. More importantly, the spectral components analyses and reconstruction uncovers the nature of luminescence and its correlation to electrical ageing. In the future, luminescence measurement can be developed to be a standard method to probe and analyze insulating polymers.L'électroluminescence (EL) de isolants polymères est étudiée car elle peut permettre d'approcher les phénomènes de vieillissement électrique en fournissant la signature optique d'espèces excitées sous champ électrique. Le vieillissement et la rupture diélectrique dans les isolants polymères est d'un intérêt fondamental pour les chercheurs, concepteurs et fabricants de dispositif du génie électrique. À cet égard, les décharges partielles (DPs) sont un des principaux processus conduisant au vieillissement et à la défaillance des isolants. Cependant, avec le développement des matériaux et procédés, les DPs sont évitées dans certaines situations, par exemple, les câbles haute tension, les condensateurs, etc. Par conséquent, le besoin reste prégnant pour la compréhension des mécanismes de dégradation électrique sous forte contrainte électrique, qui peut être initiée par des porteurs énergétiques. Dans ce travail, l'EL, la cathodoluminescence (CL) excitée sous faisceau d'électrons, ainsi que d'autres techniques de luminescence ont été appliquées à la caractérisation de polyoléfines et d'autres polymères isolants. Afin de comprendre la formation d'excitons dans des films minces de Polypropylène (PP) et Polyéthylène (PE), la dépendance en champ de l'EL et du courant sous contrainte continue, et de l'EL et de sa résolution selon la phase sous contrainte AC, sont étudiées. Les spectres d'EL du PP et du PE ont le même pic principal à environ 570 nm, ce qui implique des structures et des défauts chimiques similaires pour les deux matériaux, et le même processus de dégradation. Le pic principal peut être complété par une émission à environ 750 nm dominante à faible champ. L'impact de la nature des électrodes a été étudiée sur du PEN pour comprendre l'origine de l'émission dans le rouge. A travers la dépendance en champ de l'EL et sa résolution selon la phase avec des métallisations or et ITO, on montre que l'émission dans le rouge est liée à la nature des électrodes et correspond à l'excitation de plasmons de surface ou d'états d'interface. Une étude plus approfondie est effectuée sur la cathodoluminescence d'isolants polymères. Des couches minces de PP, PE, ainsi que de Polyethylene Naphthalate (PEN) et de Polyether Ether Ketone (PEEK) ont été irradiés par faisceau d'électrons jusqu'à 5 keV. Nous avons pu reconstruire les spectres de CL et d'EL du PE et du PP à partir de quatre composants élémentaires: fluorescence, chimiluminescence, luminescence induite par recombinaison, et composante principale du spectre d'EL à 570nm décrite plus haut et considérée comme signature du vieillissement. Pour la première fois, la nature de l'EL et de la CL de polyoléfines est décomposée en quatre composantes de base avec des contributions relatives différentes. L'identification de ces composantes spectrales est utile pour interpréter la luminescence de polyoléfines et autres isolants polymères, et établir les liens entre distribution de charge d'espace et vieillissement diélectrique. A travers ces recherches sur l'EL et la CL dans plusieurs isolants polymères, i.e. polyoléfines ou polyesters, la formation d'excitons et les processus de relaxation d'énergie sous contrainte électrique et électrons énergétiques sont mis en évidence. Surtout, l'analyse en composantes spectrales et la reconstruction des spectres donne accès aux mécanismes d'excitation de la luminescence et à une corrélation avec le vieillissement électrique. A l'avenir, les mesures de luminescence peuvent devenir une méthode standard pour sonder et analyser les isolants polymères

Label-free breast histopathology using quantitative phase imaging

According to the latest World Health Organization (WHO) statistics, breast cancer is the most common type of cancer among women worldwide. The WHO has further emphasized that early diagnosis and treatment are key in mitigating the burden of disease. In spite of this assessment, the standard histopathology of breast cancer still relies on manual microscopic examination of stained tissue. Being qualitative and manual in nature, this standard diagnostic procedure can suffer from inter-observer variation and low-throughput. In addition, stain variation between different samples and different laboratories creates problems for supervised image analysis methods for automated diagnosis. A quantitative, label-free and automatable microscopic modality for breast cancer diagnosis is, thus, needed to address these shortcomings in the standard method. Furthermore, prognostic biomarkers are important tools used by clinicians in order assess the disease course in patients. Being correlated with outcomes, these markers allow pathologists to determine aggressiveness of disease and tailor treatment accordingly. However, the current set of biomarkers for breast cancer are ineffective in predicting outcomes in all patients and there is a need for additional markers of prognosis to better account for variation among individuals. Microscopic and imaging tools for extracting new, quantitative biomarkers during breast histopathology are, thus, also desirable. Although a number of new quantitative imaging modalities for diagnostic and prognostic evaluations have been proposed, a key challenge remains compatibility with the existing workflow for easier clinical translation. Quantitative methods that minimally affect the clinical pipeline already in place are expected to have a greater impact than those that require significant new infrastructure. During my graduate work I have approached these problems in modern breast histopathology by using quantitative phase imaging (QPI). QPI is a label-free microscopy technique where image contrast is generated by measuring the optical path-length difference (OPD) across the specimen. OPD refers to the product of the refractive index and thickness at a point in the field of view. Since this measurement relies on a physical property of tissue and is label-free, it provides an objective and potentially automatable basis for tissue assessment. We employ a QPI technique called Spatial Light Interference Microscopy (SLIM) for investigations carried out during this thesis research. The specific aims of my thesis research are: 1. Label-free quantitative evaluation of breast biopsies using SLIM: In this work, we show by imaging a tissue microarray (TMA) that our QPI based method can separate benign and malignant cases by relying on tissue OPD based features. By employing image processing and statistical learning, we demonstrate a label-free quantitative diagnosis scheme that can provide an objective basis for tissue assessment. A quantitative method like this can also, potentially, be automated, reducing case-load for pathologists by automatically flagging problematic cases that require further investigation. 2. Quantifying tumor adjacent collagen structure in breast tissue using SLIM: Recent evidence shows that the structure of tumor adjacent collagen fibers influences tumor progression. In particular, collagen fiber alignment and orientation can facilitate epithelial invasion to surrounding tissue. We demonstrate that SLIM can be used to detect this prognostic marker that in the past had been detected using Second Harmonic Generation Microscopy (SHGM). Our SLIM based method improves on the SHGM based method in terms of throughput and the fact that cellular information can be obtained, in addition to collagen fiber structure, in a single image. 3. Quantitative histopathology on stained tissue biopsies: The instruments and image analysis tools developed in Aims 1 and 2 are designed for unstained tissue biopsies. Since standard tissue histopathology inevitably requires staining, we aim to demonstrate that we can extend these tools to stained tissue biopsies. In this way, the standard diagnostic workflow will be minimally disrupted. In addition, from a single shot, both an OPD map and stained tissue bright field image will be obtainable for evaluation. We demonstrate that QPI images of stained tissue can be used to solve diagnostic and prognostic problems in breast tissue assessment, using quantitative markers