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.

Path planning for image based visual servoing

This thesis deals with Visual Servoing and its strictly connected disciplines like projective geometry, image processing, robotics and non-linear control. More specifically the work addresses the problem to control a robotic manipulator through one of the largely used Visual Servoing techniques: the Image Based Visual Servoing (IBVS). In Image Based Visual Servoing the robot is driven by on-line performing a feedback control loop that is closed directly in the 2D space of the camera sensor. The work considers the case of a monocular system with the only camera mounted on the robot end effector (eye in hand configuration). Through IBVS the system can be positioned with respect to a 3D fixed target by minimizing the differences between its initial view and its goal view, corresponding respectively to the initial and the goal system configurations: the robot Cartesian Motion is thus generated only by means of visual informations. However, the execution of a positioning control task by IBVS is not straightforward because singularity problems may occur and local minima may be reached where the reached image is very close to the target one but the 3D positioning task is far from being fulfilled: this happens in particular for large camera displacements, when the the initial and the goal target views are noticeably different. To overcame singularity and local minima drawbacks, maintaining the good properties of IBVS robustness with respect to modeling and camera calibration errors, an opportune image path planning can be exploited. This work deals with the problem of generating opportune image plane trajectories for tracked points of the servoing control scheme (a trajectory is made of a path plus a time law). The generated image plane paths must be feasible i.e. they must be compliant with rigid body motion of the camera with respect to the object so as to avoid image jacobian singularities and local minima problems. In addition, the image planned trajectories must generate camera velocity screws which are smooth and within the allowed bounds of the robot. We will show that a scaled 3D motion planning algorithm can be devised in order to generate feasible image plane trajectories. Since the paths in the image are off-line generated it is also possible to tune the planning parameters so as to maintain the target inside the camera field of view even if, in some unfortunate cases, the feature target points would leave the camera images due to 3D robot motions. To test the validity of the proposed approach some both experiments and simulations results have been reported taking also into account the influence of noise in the path planning strategy. The experiments have been realized with a 6DOF anthropomorphic manipulator with a fire-wire camera installed on its end effector: the results demonstrate the good performances and the feasibility of the proposed approach.

A new snowfall detection algorithm for high latitude regions based on a combination of active and passive sensors

Precipitation retrieval over high latitudes, particularly snowfall retrieval over ice and snow, using satellite-based passive microwave spectrometers, is currently an unsolved problem. The challenge results from the large variability of microwave emissivity spectra for snow and ice surfaces, which can mimic, to some degree, the spectral characteristics of snowfall. This work focuses on the investigation of a new snowfall detection algorithm specific for high latitude regions, based on a combination of active and passive sensors able to discriminate between snowing and non snowing areas. The space-borne Cloud Profiling Radar (on CloudSat), the Advanced Microwave Sensor units A and B (on NOAA-16) and the infrared spectrometer MODIS (on AQUA) have been co-located for 365 days, from October 1st 2006 to September 30th, 2007. CloudSat products have been used as truth to calibrate and validate all the proposed algorithms. The methodological approach followed can be summarised into two different steps. In a first step, an empirical search for a threshold, aimed at discriminating the case of no snow, was performed, following Kongoli et al. [2003]. This single-channel approach has not produced appropriate results, a more statistically sound approach was attempted. Two different techniques, which allow to compute the probability above and below a Brightness Temperature (BT) threshold, have been used on the available data. The first technique is based upon a Logistic Distribution to represent the probability of Snow given the predictors. The second technique, defined Bayesian Multivariate Binary Predictor (BMBP), is a fully Bayesian technique not requiring any hypothesis on the shape of the probabilistic model (such as for instance the Logistic), which only requires the estimation of the BT thresholds. The results obtained show that both methods proposed are able to discriminate snowing and non snowing condition over the Polar regions with a probability of correct detection larger than 0.5, highlighting the importance of a multispectral approach.

Influence of processing conditions on quality aspects of potato-based fresh pasta

Gnocchi is a typical Italian potato-based fresh pasta that can be either homemade or industrially manufactured. The homemade traditional product is consumed fresh on the day it is produced, whereas the industrially manufactured one is vacuum-packed in polyethylene and usually stored at refrigerated conditions. At industrial level, most kinds of gnocchi are usually produced by using some potato derivatives (i.e. flakes, dehydrated products or flour) to which soft wheat flour, salt, some emulsifiers and aromas are added. Recently, a novel type of gnocchi emerged on the Italian pasta market, since it would be as much similar as possible to the traditional homemade one. It is industrially produced from fresh potatoes as main ingredient and soft wheat flour, pasteurized liquid eggs and salt, moreover this product undergoes steam cooking and mashing industrial treatments. Neither preservatives nor emulsifiers are included in the recipe. The main aim of this work was to get inside the industrial manufacture of gnocchi, in order to improve the quality characteristics of the final product, by the study of the main steps of the production, starting from the raw and steam cooked tubers, through the semi-finished materials, such as the potato puree and the formulated dough. For this purpose the investigation of the enzymatic activity of the raw and steam cooked potatoes, the main characteristics of the puree (colour, texture and starch), the interaction among ingredients of differently formulated doughs and the basic quality aspects of the final product have been performed. Results obtained in this work indicated that steam cooking influenced the analysed enzymes (Pectin methylesterase and α- and β-amylases) in different tissues of the tuber. PME resulted still active in the cortex, it therefore may affect the texture of cooked potatoes to be used as main ingredient in the production of gnocchi. Starch degrading enzymes (α- and β-amylases) were inactivated both in the cortex and in the pith of the tuber. The study performed on the potato puree showed that, between the two analysed samples, the product which employed dual lower pressure treatments seemed to be the most suitable to the production of gnocchi, in terms of its better physicochemical and textural properties. It did not evidence aggregation phenomena responsible of hard lumps, which may occur in this kind of semi-finished product. The textural properties of gnocchi doughs were not influenced by the different formulation as expected. Among the ingredients involved in the preparation of the different samples, soft wheat flour seemed to be the most crucial in affecting the quality features of gnocchi doughs. As a consequence of the interactive effect of the ingredients on the physicochemical and textural characteristics of the different doughs, a uniform and well-defined split-up among samples was not obtained. In the comparison of different kinds of gnocchi, the optimal physicochemical and textural properties were detected in the sample made with fresh tubers. This was probably caused not only by the use of fresh steam cooked potatoes, but also by the pasteurized liquid eggs and by the absence of any kind of emulsifier, additive or preserving substance.

Electrode Materials for Ionic Liquid Based-Supercapacitors

The development of safe, high energy and power electrochemical energy-conversion systems can be a response to the worldwide demand for a clean and low-fuel-consuming transport. This thesis work, starting from a basic studies on the ionic liquid (IL) electrolytes and carbon electrodes and concluding with tests on large-size IL-based supercapacitor prototypes demonstrated that the IL-based asymmetric configuration (AEDLCs) is a powerful strategy to develop safe, high-energy supercapacitors that might compete with lithium-ion batteries in power assist-hybrid electric vehicles (HEVs). The increase of specific energy in EDLCs was achieved following three routes: i) the use of hydrophobic ionic liquids (ILs) as electrolytes; ii) the design and preparation of carbon electrode materials of tailored morphology and surface chemistry to feature high capacitance response in IL and iii) the asymmetric double-layer carbon supercapacitor configuration (AEDLC) which consists of assembling the supercapacitor with different carbon loadings at the two electrodes in order to exploit the wide electrochemical stability window (ESW) of IL and to reach high maximum cell voltage (Vmax). Among the various ILs investigated the N-methoxyethyl-N-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide (PYR1(2O1)TFSI) was selected because of its hydrophobicity and high thermal stability up to 350 °C together with good conductivity and wide ESW, exploitable in a wide temperature range, below 0°C. For such exceptional properties PYR1(2O1)TFSI was used for the whole study to develop large size IL-based carbon supercapacitor prototype. This work also highlights that the use of ILs determines different chemical-physical properties at the interface electrode/electrolyte with respect to that formed by conventional electrolytes. Indeed, the absence of solvent in ILs makes the properties of the interface not mediated by the solvent and, thus, the dielectric constant and double-layer thickness strictly depend on the chemistry of the IL ions. The study of carbon electrode materials evidences several factors that have to be taken into account for designing performing carbon electrodes in IL. The heat-treatment in inert atmosphere of the activated carbon AC which gave ACT carbon featuring ca. 100 F/g in IL demonstrated the importance of surface chemistry in the capacitive response of the carbons in hydrophobic ILs. The tailored mesoporosity of the xerogel carbons is a key parameter to achieve high capacitance response. The CO2-treated xerogel carbon X3a featured a high specific capacitance of 120 F/g in PYR14TFSI, however, exhibiting high pore volume, an excess of IL is required to fill the pores with respect to that necessary for the charge-discharge process. Further advances were achieved with electrodes based on the disordered template carbon DTC7 with pore size distribution centred at 2.7 nm which featured a notably high specific capacitance of 140 F/g in PYR14TFSI and a moderate pore volume, V>1.5 nm of 0.70 cm3/g. This thesis work demonstrated that by means of the asymmetric configuration (AEDLC) it was possible to reach high cell voltage up to 3.9 V. Indeed, IL-based AEDLCs with the X3a or ACT carbon electrodes exhibited specific energy and power of ca. 30 Wh/kg and 10 kW/kg, respectively. The DTC7 carbon electrodes, featuring a capacitance response higher of 20%-40% than those of X3a and ACT, respectively, enabled the development of a PYR14TFSI-based AEDLC with specific energy and power of 47 Wh/kg and 13 kW/kg at 60°C with Vmax of 3.9 V. Given the availability of the ACT carbon (obtained from a commercial material), the PYR1(2O1)TFSI-based AEDLCs assembled with ACT carbon electrodes were selected within the EU ILHYPOS project for the development of large-size prototypes. This study demonstrated that PYR1(2O1)TFSI-based AEDLC can operate between -30°C and +60°C and its cycling stability was proved at 60°C up to 27,000 cycles with high Vmax up to 3.8 V. Such AEDLC was further investigated following USABC and DOE FreedomCAR reference protocols for HEV to evaluate its dynamic pulse-power and energy features. It was demonstrated that with Vmax of 3.7 V at T> 30 °C the challenging energy and power targets stated by DOE for power-assist HEVs, and at T> 0 °C the standards for the 12V-TSS and 42V-FSS and TPA 2s-pulse applications are satisfied, if the ratio wmodule/wSC = 2 is accomplished, which, however, is a very demanding condition. Finally, suggestions for further advances in IL-based AEDLC performance were found. Particularly, given that the main contribution to the ESR is the electrode charging resistance, which in turn is affected by the ionic resistance in the pores that is also modulated by pore length, the pore geometry is a key parameter in carbon design not only because it defines the carbon surface but also because it can differentially “amplify” the effect of IL conductivity on the electrode charging-discharging process and, thus, supercapacitor time constant.

Procedures of quality control and data analysis of multi-site ground-based observations for the absolute flux calibration of Gaia

The Gaia space mission is a major project for the European astronomical community. As challenging as it is, the processing and analysis of the huge data-flow incoming from Gaia is the subject of thorough study and preparatory work by the DPAC (Data Processing and Analysis Consortium), in charge of all aspects of the Gaia data reduction. This PhD Thesis was carried out in the framework of the DPAC, within the team based in Bologna. The task of the Bologna team is to define the calibration model and to build a grid of spectro-photometric standard stars (SPSS) suitable for the absolute flux calibration of the Gaia G-band photometry and the BP/RP spectrophotometry. Such a flux calibration can be performed by repeatedly observing each SPSS during the life-time of the Gaia mission and by comparing the observed Gaia spectra to the spectra obtained by our ground-based observations. Due to both the different observing sites involved and the huge amount of frames expected (≃100000), it is essential to maintain the maximum homogeneity in data quality, acquisition and treatment, and a particular care has to be used to test the capabilities of each telescope/instrument combination (through the “instrument familiarization plan”), to devise methods to keep under control, and eventually to correct for, the typical instrumental effects that can affect the high precision required for the Gaia SPSS grid (a few % with respect to Vega). I contributed to the ground-based survey of Gaia SPSS in many respects: with the observations, the instrument familiarization plan, the data reduction and analysis activities (both photometry and spectroscopy), and to the maintenance of the data archives. However, the field I was personally responsible for was photometry and in particular relative photometry for the production of short-term light curves. In this context I defined and tested a semi-automated pipeline which allows for the pre-reduction of imaging SPSS data and the production of aperture photometry catalogues ready to be used for further analysis. A series of semi-automated quality control criteria are included in the pipeline at various levels, from pre-reduction, to aperture photometry, to light curves production and analysis.

Cosmic-Lab: Optical companions to binary Millisecond Pulsars

Millisecond Pulsars (MSPs) are fast rotating, highly magnetized neutron stars. According to the "canonical recycling scenario", MSPs form in binary systems containing a neutron star which is spun up through mass accretion from the evolving companion. Therefore, the final stage consists of a binary made of a MSP and the core of the deeply peeled companion. In the last years, however an increasing number of systems deviating from these expectations has been discovered, thus strongly indicating that our understanding of MSPs is far to be complete. The identification of the optical companions to binary MSPs is crucial to constrain the formation and evolution of these objects. In dense environments such as Globular Clusters (GCs), it also allows us to get insights on the cluster internal dynamics. By using deep photometric data, acquired both from space and ground-based telescopes, we identified 5 new companions to MSPs. Three of them being located in GCs and two in the Galactic Field. The three new identifications in GCs increased by 50% the number of such objects known before this Thesis. They all are non-degenerate stars, at odds with the expectations of the "canonical recycling scenario". These results therefore suggest either that transitory phases should also be taken into account, or that dynamical processes, as exchange interactions, play a crucial role in the evolution of MSPs. We also performed a spectroscopic follow-up of the companion to PSRJ1740-5340A in the GC NGC 6397, confirming that it is a deeply peeled star descending from a ~0.8Msun progenitor. This nicely confirms the theoretical expectations about the formation and evolution of MSPs.

Automatic risk evaluation in elderly patients based on Autonomic Nervous System assessment

Dysfunction of Autonomic Nervous System (ANS) is a typical feature of chronic heart failure and other cardiovascular disease. As a simple non-invasive technology, heart rate variability (HRV) analysis provides reliable information on autonomic modulation of heart rate. The aim of this thesis was to research and develop automatic methods based on ANS assessment for evaluation of risk in cardiac patients. Several features selection and machine learning algorithms have been combined to achieve the goals. Automatic assessment of disease severity in Congestive Heart Failure (CHF) patients: a completely automatic method, based on long-term HRV was proposed in order to automatically assess the severity of CHF, achieving a sensitivity rate of 93% and a specificity rate of 64% in discriminating severe versus mild patients. Automatic identification of hypertensive patients at high risk of vascular events: a completely automatic system was proposed in order to identify hypertensive patients at higher risk to develop vascular events in the 12 months following the electrocardiographic recordings, achieving a sensitivity rate of 71% and a specificity rate of 86% in identifying high-risk subjects among hypertensive patients. Automatic identification of hypertensive patients with history of fall: it was explored whether an automatic identification of fallers among hypertensive patients based on HRV was feasible. The results obtained in this thesis could have implications both in clinical practice and in clinical research. The system has been designed and developed in order to be clinically feasible. Moreover, since 5-minute ECG recording is inexpensive, easy to assess, and non-invasive, future research will focus on the clinical applicability of the system as a screening tool in non-specialized ambulatories, in order to identify high-risk patients to be shortlisted for more complex investigations.

NLGA based Active Control in Aerospace: fault tolerability, disturbance rejection, and parameter estimation

A new control scheme has been presented in this thesis. Based on the NonLinear Geometric Approach, the proposed Active Control System represents a new way to see the reconfigurable controllers for aerospace applications. The presence of the Diagnosis module (providing the estimation of generic signals which, based on the case, can be faults, disturbances or system parameters), mean feature of the depicted Active Control System, is a characteristic shared by three well known control systems: the Active Fault Tolerant Controls, the Indirect Adaptive Controls and the Active Disturbance Rejection Controls. The standard NonLinear Geometric Approach (NLGA) has been accurately investigated and than improved to extend its applicability to more complex models. The standard NLGA procedure has been modified to take account of feasible and estimable sets of unknown signals. Furthermore the application of the Singular Perturbations approximation has led to the solution of Detection and Isolation problems in scenarios too complex to be solved by the standard NLGA. Also the estimation process has been improved, where multiple redundant measuremtent are available, by the introduction of a new algorithm, here called "Least Squares - Sliding Mode". It guarantees optimality, in the sense of the least squares, and finite estimation time, in the sense of the sliding mode. The Active Control System concept has been formalized in two controller: a nonlinear backstepping controller and a nonlinear composite controller. Particularly interesting is the integration, in the controller design, of the estimations coming from the Diagnosis module. Stability proofs are provided for both the control schemes. Finally, different applications in aerospace have been provided to show the applicability and the effectiveness of the proposed NLGA-based Active Control System.