A subpixel edge detector applied to aortic dissection detection

[EN] The aortic dissection is a disease that can cause a deadly situation, even with a correct treatment. It consists in a rupture of a layer of the aortic artery wall, causing a blood flow inside this rupture, called dissection. The aim of this paper is to contribute to its diagnosis, detecting the dissection edges inside the aorta. A subpixel accuracy edge detector based on the hypothesis of partial volume effect is used, where the intensity of an edge pixel is the sum of the contribution of each color weighted by its relative area inside the pixel. The method uses a floating window centred on the edge pixel and computes the edge features. The accuracy of our method is evaluated on synthetic images of different hickness and noise levels, obtaining an edge detection with a maximal mean error lower than 16 percent of a pixel.

Statistical methods for biomedical signal analysis and processing

Statistical modelling and statistical learning theory are two powerful analytical frameworks for analyzing signals and developing efficient processing and classification algorithms. In this thesis, these frameworks are applied for modelling and processing biomedical signals in two different contexts: ultrasound medical imaging systems and primate neural activity analysis and modelling. In the context of ultrasound medical imaging, two main applications are explored: deconvolution of signals measured from a ultrasonic transducer and automatic image segmentation and classification of prostate ultrasound scans. In the former application a stochastic model of the radio frequency signal measured from a ultrasonic transducer is derived. This model is then employed for developing in a statistical framework a regularized deconvolution procedure, for enhancing signal resolution. In the latter application, different statistical models are used to characterize images of prostate tissues, extracting different features. These features are then uses to segment the images in region of interests by means of an automatic procedure based on a statistical model of the extracted features. Finally, machine learning techniques are used for automatic classification of the different region of interests. In the context of neural activity signals, an example of bio-inspired dynamical network was developed to help in studies of motor-related processes in the brain of primate monkeys. The presented model aims to mimic the abstract functionality of a cell population in 7a parietal region of primate monkeys, during the execution of learned behavioural tasks.

Partial discharge in power distribution electrical systems: pulse propagation models and detection optimization

Investigation on impulsive signals, originated from Partial Discharge (PD) phenomena, represents an effective tool for preventing electric failures in High Voltage (HV) and Medium Voltage (MV) systems. The determination of both sensors and instruments bandwidths is the key to achieve meaningful measurements, that is to say, obtaining the maximum Signal-To-Noise Ratio (SNR). The optimum bandwidth depends on the characteristics of the system under test, which can be often represented as a transmission line characterized by signal attenuation and dispersion phenomena. It is therefore necessary to develop both models and techniques which can characterize accurately the PD propagation mechanisms in each system and work out the frequency characteristics of the PD pulses at detection point, in order to design proper sensors able to carry out PD measurement on-line with maximum SNR. Analytical models will be devised in order to predict PD propagation in MV apparatuses. Furthermore, simulation tools will be used where complex geometries make analytical models to be unfeasible. In particular, PD propagation in MV cables, transformers and switchgears will be investigated, taking into account both irradiated and conducted signals associated to PD events, in order to design proper sensors.

A Unitary Approach to Information and Estimation Theory in Digital Communication Systems

This thesis presents the outcomes of a Ph.D. course in telecommunications engineering. It is focused on the optimization of the physical layer of digital communication systems and it provides innovations for both multi- and single-carrier systems. For the former type we have first addressed the problem of the capacity in presence of several nuisances. Moreover, we have extended the concept of Single Frequency Network to the satellite scenario, and then we have introduced a novel concept in subcarrier data mapping, resulting in a very low PAPR of the OFDM signal. For single carrier systems we have proposed a method to optimize constellation design in presence of a strong distortion, such as the non linear distortion provided by satellites' on board high power amplifier, then we developed a method to calculate the bit/symbol error rate related to a given constellation, achieving an improved accuracy with respect to the traditional Union Bound with no additional complexity. Finally we have designed a low complexity SNR estimator, which saves one-half of multiplication with respect to the ML estimator, and it has similar estimation accuracy.

Confocal microscopy applied to the study of single entity fluorescence and light scattering

A sample scanning confocal optical microscope (SCOM) was designed and constructed in order to perform local measurements of fluorescence, light scattering and Raman scattering. This instrument allows to measure time resolved fluorescence, Raman scattering and light scattering from the same diffraction limited spot. Fluorescence from single molecules and light scattering from metallic nanoparticles can be studied. First, the electric field distribution in the focus of the SCOM was modelled. This enables the design of illumination modes for different purposes, such as the determination of the three-dimensional orientation of single chromophores. Second, a method for the calculation of the de-excitation rates of a chromophore was presented. This permits to compare different detection schemes and experimental geometries in order to optimize the collection of fluorescence photons. Both methods were combined to calculate the SCOM fluorescence signal of a chromophore in a general layered system. The fluorescence excitation and emission of single molecules through a thin gold film was investigated experimentally and modelled. It was demonstrated that, due to the mediation of surface plasmons, single molecule fluorescence near a thin gold film can be excited and detected with an epi-illumination scheme through the film. Single molecule fluorescence as close as 15nm to the gold film was studied in this manner. The fluorescence dynamics (fluorescence blinking and excited state lifetime) of single molecules was studied in the presence and in the absence of a nearby gold film in order to investigate the influence of the metal on the electronic transition rates. The trace-histogram and the autocorrelation methods for the analysis of single molecule fluorescence blinking were presented and compared via the analysis of Monte-Carlo simulated data. The nearby gold influences the total decay rate in agreement to theory. The gold presence produced no influence on the ISC rate from the excited state to the triplet but increased by a factor of 2 the transition rate from the triplet to the singlet ground state. The photoluminescence blinking of Zn0.42Cd0.58Se QDs on glass and ITO substrates was investigated experimentally as a function of the excitation power (P) and modelled via Monte-Carlo simulations. At low P, it was observed that the probability of a certain on- or off-time follows a negative power-law with exponent near to 1.6. As P increased, the on-time fraction reduced on both substrates whereas the off-times did not change. A weak residual memory effect between consecutive on-times and consecutive off-times was observed but not between an on-time and the adjacent off-time. All of this suggests the presence of two independent mechanisms governing the lifetimes of the on- and off-states. The simulated data showed Poisson-distributed off- and on-intensities, demonstrating that the observed non-Poissonian on-intensity distribution of the QDs is not a product of the underlying power-law probability and that the blinking of QDs occurs between a non-emitting off-state and a distribution of emitting on-states with different intensities. All the experimentally observed photo-induced effects could be accounted for by introducing a characteristic lifetime tPI of the on-state in the simulations. The QDs on glass presented a tPI proportional to P-1 suggesting the presence of a one-photon process. Light scattering images and spectra of colloidal and C-shaped gold nano-particles were acquired. The minimum size of a metallic scatterer detectable with the SCOM lies around 20 nm.

Development of bionanotechnological strategies for signal enhancement in nucleic acids biosensors

Nucleic acid biosensors represent a powerful tool for clinical and environmental pathogens detection. For applications such as point-of-care biosensing, it is fundamental to develop sensors that should be automatic, inexpensive, portable and require a professional skill of the user that should be as low as possible. With the goal of determining the presence of pathogens when present in very small amount, such as for the screening of pathogens in drinking water, an amplification step must be implemented. Often this type of determinations should be performed with simple, automatic and inexpensive hardware: the use of a chemical (or nanotechnological) isothermal solution would be desirable. My Ph.D. project focused on the study and on the testing of four isothermal reactions which can be used to amplify the nucleic acid analyte before the binding event on the surface sensor or to amplify the signal after that the hybridization event with the probe. Recombinase polymerase amplification (RPA) and ligation-mediated rolling circle amplification (L-RCA) were investigated as methods for DNA and RNA amplification. Hybridization chain reaction (HCR) and Terminal deoxynucleotidil transferase-mediated amplification were investigated as strategies to achieve the enhancement of the signal after the surface hybridization event between target and probe. In conclusion, it can be said that only a small subset of the biochemical strategies that are proved to work in solution towards the amplification of nucleic acids does truly work in the context of amplifying the signal of a detection system for pathogens. Amongst those tested during my Ph.D. activity, recombinase polymerase amplification seems the best candidate for a useful implementation in diagnostic or environmental applications.

Recombinant expression of molluscan hemocyanin (KLH) substructures in a prokaryotic system: E. coli

The recombinant expression of 19 different substructures of KLH in the prokaryotic sys-tem E. coli has been successfully achieved: each one of the eight single FUs a to h of both isoforms, KLH1 and KLH2, two substructures consisting of two consecutive FUs (KLH1-bc and KLH1-gh) as well as a cDNA encompassing KLH1-abc. All recombinant proteins, fused to an N-terminal 6xHis tag, have successfully been detected by immuno precipitation using monoclonal α-His-antibodies and polyclonal α-KLH1- and α-KLH2-antibodies. One exception remained: SP-KLH2-a, which was not detected by the α-His-antibodies. This allows speculations as to whether the coexpressed signal peptide can lead, at one hand, to the secretion of the recombinant protein, and on the other to the simultaneous cut-off of the leader peptide, which results in the splitting off of even more N-terminal 6xHis tag, leading to failed recognition by the appropriate antibodies. The comparison of native KLH with recombinantly expressed prokaryotic (E. coli) and eukaryotic (Sf9 insect cells) KLH was done using FU-1h. The weak detection by the polyclonal α-KLH1-antibodies of both recombinantly expressed proteins showed that the native protein was the best recognized. For the prokaryotic one, both the denaturation applied for solubilisation of the bacterial inclusion bodies and the inability of bacterial cells to add N-linked glycosylation, are the reason for the poor hybridization. In contrast, KLH1-h expressed in eukaryotic insect cells is likely to be glycosylated. The incubation with the α-KLH1-antibodies resulting in the same weak detection, however, revealed that the linked carbohydrate side chains are not those expected. The establishment of SOE-PCR, together with further improvement, has enabled the generation of a clone encompassing the complete subunit KLH1-abcdefgh. The se-quence analysis compared to the original KLH1 sequence showed, however, that the resulting recombinant protein is defective in two histidines, required for the copper bind-ing sites in FU-1b and FU-1d and in three disulfide bridges (FU-1a, FU-1b and FU 1g). This is due to polymerase-related nucleotide exchanges, resulting in a changed amino acid sequence. Nevertheless, all eight potential N-glycosylation sites are present, leading to the speculation that the recombinant protein can in theory be fully glycosylated, which is the most important aspect for the clinical applicability of recombinant KLH as an im-munotherapeutic agent. The improvement of this method elaborated during the present work indicates bright prospects for the future generation of a correct cDNA sequence encoding for the complete KLH2 subunit.

NMR spectroscopy and imaging of hyperpolarized gases

Since the discovery of the nuclear magnetic resonance (NMR) phenomenon, countless NMR techniques have been developed that are today indispensable tools in physics, chemistry, biology, and medicine. As one of the main obstacles in NMR is its notorious lack of sensitivity, different hyperpolarization (HP) methods have been established to increase signals up to several orders of magnitude. In this work, different aspects of magnetic resonance, using HP noble gases, are studied, hereby combining different disciplines of research. The first part examines new fundamental effects in NMR of HP gases, in theory and experiment. The spin echo phenomenon, which provides the basis of numerous modern experiments, is studied in detail in the gas phase. The changes of the echo signal in terms of amplitude, shape, and position, due to the fast translational motion, are described by an extension of the existing theory and computer simulations. With this knowledge as a prerequisite, the detection of intermolecular double-quantum coherences was accomplished for the first time in the gas phase. The second part of this thesis focuses on the development of a practical method to enhance the dissolution process of HP 129Xe, without loss of polarization or shortening of T1. Two different setups for application in NMR spectroscopy and magnetic resonance imaging (MRI) are presented. The continuous operation allows biological and multidimensional spectroscopy in solutions. Also, first in vitro MRI images with dissolved HP 129Xe as contrast agent were obtained at a clinical scanner.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

A parallel community detection algorithm

Complex networks analysis is a very popular topic in computer science. Unfortunately this networks, extracted from different contexts, are usually very large and the analysis may be very complicated: computation of metrics on these structures could be very complex. Among all metrics we analyse the extraction of subnetworks called communities: they are groups of nodes that probably play the same role within the whole structure. Communities extraction is an interesting operation in many different fields (biology, economics,...). In this work we present a parallel community detection algorithm that can operate on networks with huge number of nodes and edges. After an introduction to graph theory and high performance computing, we will explain our design strategies and our implementation. Then, we will show some performance evaluation made on a distributed memory architectures i.e. the supercomputer IBM-BlueGene/Q "Fermi" at the CINECA supercomputing center, Italy, and we will comment our results.

Electrochemical sensing strategies for the detection of interactions between biological macromolecules

Electrochemical biosensors provide an attractive means to analyze the content of a biological sample due to the direct conversion of a biological event to an electronic signal, enabling the development of cheap, small, portable and simple devices, that allow multiplex and real-time detection. At the same time nanobiotechnology is drastically revolutionizing the biosensors development and different transduction strategies exploit concepts developed in these field to simplify the analysis operations for operators and end users, offering higher specificity, higher sensitivity, higher operational stability, integrated sample treatments and shorter analysis time. The aim of this PhD work has been the application of nanobiotechnological strategies to electrochemical biosensors for the detection of biological macromolecules. Specifically, one project was focused on the application of a DNA nanotechnology called hybridization chain reaction (HCR), to amplify the hybridization signal in an electrochemical DNA biosensor. Another project on which the research activity was focused concerns the development of an electrochemical biosensor based on a biological model membrane anchored to a solid surface (tBLM), for the recognition of interactions between the lipid membrane and different types of target molecules.

Efficient ultrasonic signal processing techniques for aided medical diagnostics

Ultrasound imaging is widely used in medical diagnostics as it is the fastest, least invasive, and least expensive imaging modality. However, ultrasound images are intrinsically difficult to be interpreted. In this scenario, Computer Aided Detection (CAD) systems can be used to support physicians during diagnosis providing them a second opinion. This thesis discusses efficient ultrasound processing techniques for computer aided medical diagnostics, focusing on two major topics: (i) Ultrasound Tissue Characterization (UTC), aimed at characterizing and differentiating between healthy and diseased tissue; (ii) Ultrasound Image Segmentation (UIS), aimed at detecting the boundaries of anatomical structures to automatically measure organ dimensions and compute clinically relevant functional indices. Research on UTC produced a CAD tool for Prostate Cancer detection to improve the biopsy protocol. In particular, this thesis contributes with: (i) the development of a robust classification system; (ii) the exploitation of parallel computing on GPU for real-time performance; (iii) the introduction of both an innovative Semi-Supervised Learning algorithm and a novel supervised/semi-supervised learning scheme for CAD system training that improve system performance reducing data collection effort and avoiding collected data wasting. The tool provides physicians a risk map highlighting suspect tissue areas, allowing them to perform a lesion-directed biopsy. Clinical validation demonstrated the system validity as a diagnostic support tool and its effectiveness at reducing the number of biopsy cores requested for an accurate diagnosis. For UIS the research developed a heart disease diagnostic tool based on Real-Time 3D Echocardiography. Thesis contributions to this application are: (i) the development of an automated GPU based level-set segmentation framework for 3D images; (ii) the application of this framework to the myocardium segmentation. Experimental results showed the high efficiency and flexibility of the proposed framework. Its effectiveness as a tool for quantitative analysis of 3D cardiac morphology and function was demonstrated through clinical validation.

Structured antibody surfaces for bio-recognition and a label-free detection of bacteria

Antibody microarrays are of great research interest because of their potential application as biosensors for high-throughput protein and pathogen screening technologies. In this active area, there is still a need for novel structures and assemblies providing insight in binding interactions such as spherical and annulus-shaped protein structures, e.g. for the utilization of curved surfaces for the enhanced protein-protein interactions and detection of antigens. Therefore, the goal of the presented work was to establish a new technique for the label-free detection of bio-molecules and bacteria on topographically structured surfaces, suitable for antibody binding.rnIn the first part of the presented thesis, the fabrication of monolayers of inverse opals with 10 μm diameter and the immobilization of antibodies on their interior surface is described. For this purpose, several established methods for the linking of antibodies to glass, including Schiff bases, EDC/S-NHS chemistry and the biotin-streptavidin affinity system, were tested. The employed methods included immunofluorescence and image analysis by phase contrast microscopy. It could be shown that these methods were not successful in terms of antibody immobilization and adjacent bacteria binding. Hence, a method based on the application of an active-ester-silane was introduced. It showed promising results but also the need for further analysis. Especially the search for alternative antibodies addressing other antigens on the exterior of bacteria will be sought-after in the future.rnAs a consequence of the ability to control antibody-functionalized surfaces, a new technique employing colloidal templating to yield large scale (~cm2) 2D arrays of antibodies against E. coli K12, eGFP and human integrin αvβ3 on a versatile useful glass surface is presented. The antibodies were swept to reside around the templating microspheres during solution drying, and physisorbed on the glass. After removing the microspheres, the formation of annuli-shaped antibody structures was observed. The preserved antibody structure and functionality is shown by binding the specific antigens and secondary antibodies. The improved detection of specific bacteria from a crude solution compared to conventional “flat” antibody surfaces and the setting up of an integrin-binding platform for targeted recognition and surface interactions of eukaryotic cells is demonstrated. The structures were investigated by atomic force, confocal and fluorescence microscopy. Operational parameters like drying time, temperature, humidity and surfactants were optimized to obtain a stable antibody structure.

Test der Speziellen Relativitätstheorie mittels Laserspektroskopie an relativistischen 7 Li +-Ionen am ESR

Die Invarianz physikalischer Gesetze unter Lorentztransformationen ist eines der fundamentalen Postulate der modernen Physik und alle Theorien der grundlegenden Wechselwirkungen sind in kovarianter Form formuliert. Obwohl die Spezielle Relativitätstheorie (SRT) in einer Vielzahl von Experimenten mit hoher Genauigkeit überprüft und bestätigt wurde, sind aufgrund der weitreichenden Bedeutung dieses Postulats weitere verbesserte Tests von grundsätzlichem Interesse. Darüber hinaus weisen moderne Ansätze zur Vereinheitlichung der Gravitation mit den anderen Wechselwirkungen auf eine mögliche Verletzung der Lorentzinvarianz hin. In diesem Zusammenhang spielen Ives-Stilwell Experimente zum Test der Zeitdilatation in der SRT eine bedeutende Rolle. Dabei wird die hochauflösende Laserspektroskopie eingesetzt, um die Gültigkeit der relativistischen Dopplerformel – und damit des Zeitdilatationsfaktors γ – an relativistischen Teilchenstrahlen zu untersuchen. Im Rahmen dieser Arbeit wurde ein Ives-Stilwell Experiment an 7Li+-Ionen, die bei einer Geschwindigkeit von 34 % der Lichtgeschwindigkeit im Experimentierspeicherring (ESR) des GSI Helmholtzzentrums für Schwerionenforschung gespeichert waren, durchgeführt. Unter Verwendung des 1s2s3S1→ 1s2p3P2-Übergangs wurde sowohl Λ-Spektroskopie als auch Sättigungsspektroskopie betrieben. Durch die computergestützte Analyse des Fluoreszenznachweises und unter Verwendung optimierter Kantenfilter für den Nachweis konnte das Signal zu Rauschverhältnis entscheidend verbessert und unter Einsatz eines zusätzlichen Pumplasers erstmals ein Sättigungssignal beobachtet werden. Die Frequenzstabilität der beiden verwendeten Lasersysteme wurde mit Hilfe eines Frequenzkamms spezifiziert, um eine möglichst hohe Genauigkeit zu erreichen. Die aus den Strahlzeiten gewonnen Daten wurden im Rahmen der Robertson-Mansouri-Sexl-Testtheorie (RMS) und der Standard Model Extension (SME) interpretiert und entsprechende Obergrenzen für die relevanten Testparameter der jeweiligen Theorie bestimmt. Die Obergrenze für den Testparameter α der RMS-Theorie konnte gegenüber den früheren Messungen bei 6,4 % der Lichtgeschwindigkeit am Testspeicherring (TSR) des Max-Planck-Instituts für Kernphysik in Heidelberg um einen Faktor 4 verbessert werden.