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.

Reverse Engineering tools: development and experimentation of innovative methods for physical and geometrical data integration and post-processing

In recent years, the use of Reverse Engineering systems has got a considerable interest for a wide number of applications. Therefore, many research activities are focused on accuracy and precision of the acquired data and post processing phase improvements. In this context, this PhD Thesis deals with the definition of two novel methods for data post processing and data fusion between physical and geometrical information. In particular a technique has been defined for error definition in 3D points’ coordinates acquired by an optical triangulation laser scanner, with the aim to identify adequate correction arrays to apply under different acquisition parameters and operative conditions. Systematic error in data acquired is thus compensated, in order to increase accuracy value. Moreover, the definition of a 3D thermogram is examined. Object geometrical information and its thermal properties, coming from a thermographic inspection, are combined in order to have a temperature value for each recognizable point. Data acquired by an optical triangulation laser scanner are also used to normalize temperature values and make thermal data independent from thermal-camera point of view.

The effect of diffusion gradient direction number on tractography of corticospinal tract in human brain: an along-tract analysis

Nel presente lavoro di tesi ho sviluppato un metodo di analisi di dati di DW-MRI (Diffusion-Weighted Magnetic Resonance Imaging)cerebrale, tramite un algoritmo di trattografia, per la ricostruzione del tratto corticospinale, in un campione di 25 volontari sani. Il diffusion tensor imaging (DTI) sfrutta la capacità del tensore di diffusione D di misurare il processo di diffusione dell’acqua, per stimare quantitativamente l’anisotropia dei tessuti. In particolare, nella sostanza bianca cerebrale la diffusione delle molecole di acqua è direzionata preferenzialmente lungo le fibre, mentre è ostacolata perpendicolarmente ad esse. La trattografia utilizza le informazioni ottenute tramite il DW imaging per fornire una misura della connettività strutturale fra diverse regioni del cervello. Nel lavoro si è concentrata l’attenzione sul fascio corticospinale, che è coinvolto nella motricità volontaria, trasmettendo gli impulsi dalla corteccia motoria ai motoneuroni del midollo spinale. Il lavoro si è articolato in 3 fasi. Nella prima ho sviluppato il pre-processing di immagini DW acquisite con un gradiente di diffusione sia 25 che a 64 direzioni in ognuno dei 25 volontari sani. Si è messo a punto un metodo originale ed innovativo, basato su “Regions of Interest” (ROIs), ottenute attraverso la segmentazione automatizzata della sostanza grigia e ROIs definite manualmente su un template comune a tutti i soggetti in esame. Per ricostruire il fascio si è usato un algoritmo di trattografia probabilistica che stima la direzione più probabile delle fibre e, con un numero elevato di direzioni del gradiente, riesce ad individuare, se presente, più di una direzione dominante (seconda fibra). Nella seconda parte del lavoro, ciascun fascio è stato suddiviso in 100 segmenti (percentili). Sono stati stimati anisotropia frazionaria (FA), diffusività media, probabilità di connettività, volume del fascio e della seconda fibra con un’analisi quantitativa “along-tract”, per ottenere un confronto accurato dei rispettivi percentili dei fasci nei diversi soggetti. Nella terza parte dello studio è stato fatto il confronto dei dati ottenuti a 25 e 64 direzioni del gradiente ed il confronto del fascio fra entrambi i lati. Dall’analisi statistica dei dati inter-subject e intra-subject è emersa un’elevata variabilità tra soggetti, dimostrando l’importanza di parametrizzare il tratto. I risultati ottenuti confermano che il metodo di analisi trattografica del fascio cortico-spinale messo a punto è risultato affidabile e riproducibile. Inoltre, è risultato che un’acquisizione con 25 direzioni di DTI, meglio tollerata dal paziente per la minore durata dello scan, assicura risultati attendibili. La principale applicazione clinica riguarda patologie neurodegenerative con sintomi motori sia acquisite, quali sindromi parkinsoniane sia su base genetica o la valutazione di masse endocraniche, per la definizione del grado di contiguità del fascio. Infine, sono state poste le basi per la standardizzazione dell’analisi quantitativa di altri fasci di interesse in ambito clinico o di studi di ricerca fisiopatogenetica.

Parallel vector processing of multidimensional orthogonal transforms for digital signal processing applications

The performance of the parallel vector implementation of the one- and two-dimensional orthogonal transforms is evaluated. The orthogonal transforms are computed using actual or modified fast Fourier transform (FFT) kernels. The factors considered in comparing the speed-up of these vectorized digital signal processing algorithms are discussed and it is shown that the traditional way of comparing th execution speed of digital signal processing algorithms by the ratios of the number of multiplications and additions is no longer effective for vector implementation; the structure of the algorithm must also be considered as a factor when comparing the execution speed of vectorized digital signal processing algorithms. Simulation results on the Cray X/MP with the following orthogonal transforms are presented: discrete Fourier transform (DFT), discrete cosine transform (DCT), discrete sine transform (DST), discrete Hartley transform (DHT), discrete Walsh transform (DWHT), and discrete Hadamard transform (DHDT). A comparison between the DHT and the fast Hartley transform is also included.(34 refs)

Moving along the mental number line: Interactions between whole-body motion and numerical cognition

Active head turns to the left and right have recently been shown to influence numerical cognition by shifting attention along the mental number line. In the present study, we found that passive whole-body motion influences numerical cognition. In a random-number generation task (Experiment 1), leftward and downward displacement of participants facilitated small number generation, whereas rightward and upward displacement facilitated the generation of large numbers. Influences of leftward and rightward motion were also found for the processing of auditorily presented numbers in a magnitude-judgment task (Experiment 2). Additionally, we investigated the reverse effect of the number-space association (Experiment 3). Participants were displaced leftward or rightward and asked to detect motion direction as fast as possible while small or large numbers were auditorily presented. When motion detection was difficult, leftward motion was detected faster when hearing small number and rightward motion when hearing large number. We provide new evidence that bottom-up vestibular activation is sufficient to interact with the higher-order spatial representation underlying numerical cognition. The results show that action planning or motor activity is not necessary to influence spatial attention. Moreover, our results suggest that self-motion perception and numerical cognition can mutually influence each other.

Cathepsin S dominates autoantigen processing in human thymic dendritic cells

The interaction of developing thymocytes with peptide-MHC complexes on thymic antigen presenting cells (APC) is crucial for T cell development, both for positive selection of "useful" thymocytes as well as negative selection of autoreactive thymocytes to prevent autoimmunity. The peptides presented on MHC II molecules are generated by lysosomal proteases such as the cathepsins. At the same time, lysosomal proteases will also destroy other potential T cell epitopes from self-antigens. This will lead to a lack of presentation on negatively selecting thymic antigen presenting cells and consequently, escape of autoreactive T cells recognizing these epitopes. In order to understand the processes that govern generation or destruction of self-epitopes in thymic APC, we studied the antigen processing machinery and epitope processing in the human thymus. We find that each type of thymic APC expresses a different signature of lysosomal proteases, providing indirect evidence that positive and negative selection of CD4(+) T cells might occur on different sets of peptides, in analogy to what has been proposed for CD8(+) T cells. We also find that myeloid dendritic cells (DC) are more efficient in processing autoantigen than plasmacytoid DC. In addition, we observed that cathepsin S plays a central role in processing of the autoantigens myelin basic protein and proinsulin in thymic dendritic cells. Cathepsin S destroyed a number of known T cell epitopes, which would be expected to result in lack of presentation and consequently, escape of autoreactive T cells. Cathepsin S therefore appears to be an important factor that influences selection of autoreactive T cells.

Effect Of Confined Impinging Jet Mixing Processing Parameters On Poly (Lactic Acid) Nanoparticle Morphology

Biodegradable nanoparticles are at the forefront of drug delivery research as they provide numerous advantages over traditional drug delivery methods. An important factor affecting the ability of nanoparticles to circulate within the blood stream and interact with cells is their morphology. In this study a novel processing method, confined impinging jet mixing, was used to form poly (lactic acid) nanoparticles through a solvent-diffusion process with Pluronic F-127 being used as a stabilizing agent. This study focused on the effects of Reynolds number (flow rate), surfactant presence in mixing, and polymer concentration on the morphology of poly (lactic acid) nanoparticles. In addition to looking at the parameters affecting poly (lactic acid) morphology, this study attempted to improve nanoparticle isolation and purification methods to increase nanoparticle yield and ensure specific morphologies were not being excluded during isolation and purification. The isolation and purification methods used in this study were centrifugation and a stir cell. This study successfully produced particles having pyramidal and cubic morphologies. Despite successful production of these morphologies the yield of non-spherical particles was very low, additionally great variability existed between redundant trails. Surfactant was determined to be very important for the stabilization of nanoparticles in solution but appears to be unnecessary for the formation of nanoparticles. Isolation and purification methods that produce a high yield of surfactant free particles have still not been perfected and additional testing will be necessary for improvement.¿

A MULTILEVEL MODEL TO ADDRESS BATCH EFFECTS IN COPY NUMBER ESTIMATION USING SNP ARRAYS

Submicroscopic changes in chromosomal DNA copy number dosage are common and have been implicated in many heritable diseases and cancers. Recent high-throughput technologies have a resolution that permits the detection of segmental changes in DNA copy number that span thousands of basepairs across the genome. Genome-wide association studies (GWAS) may simultaneously screen for copy number-phenotype and SNP-phenotype associations as part of the analytic strategy. However, genome-wide array analyses are particularly susceptible to batch effects as the logistics of preparing DNA and processing thousands of arrays often involves multiple laboratories and technicians, or changes over calendar time to the reagents and laboratory equipment. Failure to adjust for batch effects can lead to incorrect inference and requires inefficient post-hoc quality control procedures that exclude regions that are associated with batch. Our work extends previous model-based approaches for copy number estimation by explicitly modeling batch effects and using shrinkage to improve locus-specific estimates of copy number uncertainty. Key features of this approach include the use of diallelic genotype calls from experimental data to estimate batch- and locus-specific parameters of background and signal without the requirement of training data. We illustrate these ideas using a study of bipolar disease and a study of chromosome 21 trisomy. The former has batch effects that dominate much of the observed variation in quantile-normalized intensities, while the latter illustrates the robustness of our approach to datasets where as many as 25% of the samples have altered copy number. Locus-specific estimates of copy number can be plotted on the copy-number scale to investigate mosaicism and guide the choice of appropriate downstream approaches for smoothing the copy number as a function of physical position. The software is open source and implemented in the R package CRLMM available at Bioconductor (http:www.bioconductor.org).

EXTRACTION OF PICTORIAL ENERGY INFORMATION FROM CAMPUS UNMETERED BUILDINGS USING IMAGE PROCESSING TECHNIQUES

In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period.

RNA-dependent genome processing during nuclear differentiation: the model systems of stichotrichous ciliates

We introduce ciliated protozoa, and more specifically the stichotrichous ciliates Oxytricha and Stylonychia, as biological model systems for the analysis of programmed DNA-reorganization processes during nuclear differentiation. These include DNA excision, DNA elimination, reordering of gene segments and specific gene amplification. We show that small nuclear RNAs specify DNA sequences to be excised or retained, but also discuss the need for a RNA template molecule derived from the parental nucleus for these processes. This RNA template guides reordering of gene segments to become functional genes and determines gene copy number in the differentiated nucleus. Since the template is derived from the parental macronucleus, gene reordering and DNA amplification are inherited in a non-Mendelian epigenetic manner.

Is complex signal processing for bone conduction hearing aids useful?

OBJECTIVES To establish whether complex signal processing is beneficial for users of bone anchored hearing aids. METHODS Review and analysis of two studies from our own group, each comparing a speech processor with basic digital signal processing (either Baha Divino or Baha Intenso) and a processor with complex digital signal processing (either Baha BP100 or Baha BP110 power). The main differences between basic and complex signal processing are the number of audiologist accessible frequency channels and the availability and complexity of the directional multi-microphone noise reduction and loudness compression systems. RESULTS Both studies show a small, statistically non-significant improvement of speech understanding in quiet with the complex digital signal processing. The average improvement for speech in noise is +0.9 dB, if speech and noise are emitted both from the front of the listener. If noise is emitted from the rear and speech from the front of the listener, the advantage of the devices with complex digital signal processing as opposed to those with basic signal processing increases, on average, to +3.2 dB (range +2.3 … +5.1 dB, p ≤ 0.0032). DISCUSSION Complex digital signal processing does indeed improve speech understanding, especially in noise coming from the rear. This finding has been supported by another study, which has been published recently by a different research group. CONCLUSIONS When compared to basic digital signal processing, complex digital signal processing can increase speech understanding of users of bone anchored hearing aids. The benefit is most significant for speech understanding in noise.

Processing 20 years of SLR observations to GNSS satellites

We process 20 years of SLR observations to GPS and GLONASS satellites using the reprocessed 3-day and 1-day microwave orbits provided by the Center for Orbit Determination in Europe (CODE) for the period 1994-2013. We study the dependency of the SLR residuals on the type, size, and a number of corner cubes in satellite laser reflector arrays (LRA). We show that the mean SLR residuals and the RMS of residuals depend on the coating of LRA and the block or type of GNSS satellites. The SLR mean residuals are also a function of the equipment used at SLR stations including detector types and detecting modes.

Revisiting labour and gender issues in Export Processing Zones : the cases of South Korea, Bangladesh and India

The establishment of Export Processing Zones (EPZs) is a strategy for economic development that was introduced almost fifty years ago and is nowadays employed in a large number of countries. While the number of EPZs including several variants such as Special Economic Zone (SEZs) has increased continuously, general interest in EPZs has declined over the years in contrast to earlier heated debates regarding the efficacy of the strategy and its welfare effects especially on women workers. This article re-evaluates the historical trajectories and outstanding labour and gender issues of EPZs on the basis of the experiences of South Korea, Bangladesh and India. The findings suggest the necessity of enlarging our analytical scope with regard to EPZs, which are inextricably connected with external employment structures, whether outside the EPZ but within the same country, or outside the EPZ and its host country altogether.

Image Processing Challenges in the Creation of Spatiotemporal Gene Expression Atlases of Developing Embryos

To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.