Davide Moroni

Automatic computation of left ventricle ejection fraction from dynamic ultrasound images

Left Ventricle (LV) Ejection Fraction (EF) is a fundamental parameter for heart function assessment. Being based on border tracing, however, manual computation of EF is time-consuming and extremely prone to inter-and intraobserver variability. In this paper we present an automatic method for EF computation which provides results in agreement with those provided by expert observers. The segmentation strategy consists of two stages: first, the region of interest is identified by means of mimetic criteria; then, the identified region is used for initialization of an active contour based on a variational formulation of level set methods, which provides accurate segmentation of the LV cavity. Volume calculation is then performed according to the conventional Simpson’s rule and, finally, the EF is computed.

Quantification of Epicardial Fat by Cardiac CT Imaging

The aim of this work is to introduce and design image processing methods for the quantitative analysis of epicardial fat by using cardiac CT imaging. Indeed, epicardial fat has recently been shown to correlate with cardiovascular disease, cardiovascular risk factors and metabolic syndrome. However, many concerns still remain about the methods for measuring epicardial fat, its regional distribution on the myocardium and the accuracy and reproducibility of the measurements. In this paper, a method is proposed for the analysis of single-frame 3D images obtained by the standard acquisition protocol used for coronary calcium scoring. In the design of the method, much attention has been payed to the minimization of user intervention and to reproducibility issues. In particular, the proposed method features a two step segmentation algorithm suitable for the analysis of epicardial fat. In the first step of the algorithm, an analysis of epicardial fat intensity distribution is carried out in order to define suitable thresholds for a first rough segmentation. In the second step, a variational formulation of level set methods - including a specially-designed region homogeneity energy based on Gaussian mixture models- is used to recover spatial coherence and smoothness of fat depots. Experimental results show that the introduced method may be efficiently used for the quantification of epicardial fat.

Thesaurus project: design of new autonomous underwater vehicles for documentation and protection of underwater archaeological sites

The Thesaurus Project, funded by the Regione Toscana, combines humanistic and technological research aiming at developing a new generation of cooperating Autonomous Underwater Vehicles and at documenting ancient and modern Tuscany shipwrecks. Technological research will allow performing an archaeological exploration mission through the use of a swarm of autonomous, smart and self-organizing underwater vehicles. Using acoustic communications, these vehicles will be able to exchange each other data related to the state of the exploration and then to adapt their behavior to improve the survey. The archival research and archaeological survey aim at collecting all reports related to the underwater evidences and the events of sinking occurred in the sea of Tuscany. The collected data will be organized in a specific database suitably modeled.

Visual sensor networks for infomobility

The wide availability of embedded sensor platforms and low-cost cameras—together with the developments in wireless communication—make it now possible the conception of pervasive intelligent systems based on vision. Such systems may be understood as distributed and collaborative sensor networks, able to produce, aggregate and process images in order to understand the observed scene and communicate the relevant information found about it. In this paper, we investigate the peculiarities of visual sensor networks with respect to standard vision systems and we identify possible strategies to accomplish image processing and analysis tasks over them. Although the rather strong constraints in computational and transmission power of embedded platforms that may prevent the use of state of the art computer vision and pattern recognition methods, we argue that multi-node processing methods may be envisaged to decompose a complex task into a hierarchy of computationally simpler problems to be solved over the nodes of the network. These ideas are illustrated by describing an application of visual sensor network to infomobility. In particular, we consider an experimental setting in which several views of a parking lot are acquired by the sensor nodes in the network. By integrating the various views, the network is capable to provide a description of the scene in terms of the available spaces in the parking lot.

Underwater Scene Understanding by Optical and Acoustic Data Integration

A new method is proposed to integrate 3D optical and acoustic images relative to the same underwater environment. The combination of optical and acoustic sensors in terms of uniform reference system, geo-referencing and time allows: (i) integration cascade (operational level), (ii) safety data acquisition in various domains (distance from ground, turbid water, vegetation, etc.), (iii) replanning of missions in progress. Furthermore, data fusion can be faced according to different approaches: (a) stratification of referenced data layers, (b) correlation of quantities of different nature, (c) comparison of extracted features: 2D geometries (segments, elementary curves) and 3D (planes, simple surfaces), repetitive patterns, (d) integration of semantic information, (e) template matching for recognizing known structures, (f) creation and refinement of probability maps as a measure of optical (geometry, texture) and acoustic (elevation or reflectivity maps) properties. A set of geometrical and textural feature ...

The K(p,1) problem for the affine Artin group of type Bn and its cohomology

In this paper we prove that the complement to the affine complex arrangement of type \widetilde{B}_n is a K(\pi, 1) space. We also compute the cohomology of the affine Artin group G of type \widetilde{B}_n with coefficients over several interesting local systems. In particular, we consider the module Q[q^{\pm 1}, t^{\pm 1}], where the first n-standard generators of G act by (-q)-multiplication while the last generator acts by (-t)-multiplication. Such representation generalizes the analog 1-parameter representation related to the bundle structure over the complement to the discriminant hypersurface, endowed with the monodromy action of the associated Milnor fibre. The cohomology of G with trivial coefficients is derived from the previous one.

Biomedical Signal and Image Processing for Decision Support in Heart Failure

Signal and imaging investigations are currently a basic step of the diagnostic, prognostic and follow-up processes of heart diseases. Besides, the need of a more efficient, cost-effective and personalized care has lead nowadays to a renaissance of clinical decision support systems (CDSS). The purpose of this paper is to present an effective way to achieve a high-level integration of signal and image processing methods in the general process of care, by means of a clinical decision support system, and to discuss the advantages of such an approach. Among several heart diseases, we treat heart failure, that for its complexity highlights best the benefits of this integration. Architectural details of the related components of the CDSS are provided with special attention to their seamless integration in the general IT infrastructure. In particular, significant and suitably designed image and signal processing algorithms are introduced to objectively and reliably evaluate important features that, in collaboration with the CDSS, can facilitate decisional problems in the heart failure domain. Furthermore, additional signal and image processing tools enrich the model baseof the CDSS.

Heart deformation pattern analysis through shape modelling

In this paper, we present an approach to the description of time-varying anatomical structures. The main goal is to compactly but faithfully describe the whole heart cycle in such a way to allow for deformation pattern characterization and assessment. Using such an encoding, a reference database can be built, thus permitting similarity searches or data mining procedures.

Multi-scale Representation and Persistency for Shape Description

Extraction, organization and exploitation of topological features are emerging topics in computer vision and graphics. However, such kind of features often exhibits weak robustness with respect to small perturbations and it is often unclear how to distinguish truly topological features from topological noise. In this paper, we present an introduction to persistence theory, which aims at analyzing multi-scale representations from a topological point of view. Besides, we extend the ideas of persistency to a more general setting by defining a set of discrete invariants.

MRI left ventricle segmentation and reconstruction for the study of the heart dynamics

A two-stage method for left ventricle (LV) segmentation in magnetic resonance imaging (MRI) is reported as the current results of an ongoing research carried on within a project devoted to the analysis and study of the cardiac dynamics. The first stage of the proposed method for LV segmentation is focused on the identification and localization of the left ventricle cavity, by means of fuzzy clustering and temporal regions tracking. The final segmentation is accomplished by a second processing stage, devoted to identify the left ventricle contours using an artificial neural network