Feature based estimation of myocardial motion from tagged MR images

In the past few years we witnessed an increase in mortality due to cancer relative to mortality due to cardiovascular diseases. In 2008, the Netherlands Statistics Agency reports that 33.900 people died of cancer against 33.100 deaths due to cardiovascular diseases, making cancer the number one cause of death in the Netherlands [33]. Even if the rate of people affected by heart diseases is continually rising, they "simply don’t die of it", according to the research director Prof. Mat Daemen of research institute CARIM of the University of Maastricht [50]. The reason for this is the early diagnosis, and the treatment of people with identified risk factors for diseases like ischemic heart disease, hypertrophic cardiomyopathy, thoracic aortic disease, pericardial (sac around the heart) disease, cardiac tumors, pulmonary artery disease, valvular disease, and congenital heart disease before and after surgical repair. Cardiac imaging plays a crucial role in the early diagnosis, since it allows the accurate investigation of a large amount of imaging data in a small amount of time. Moreover, cardiac imaging reduces costs of inpatient care, as has been shown in recent studies [77]. With this in mind, in this work we have provided several tools with the aim to help the investigation of the cardiac motion. In chapters 2 and 3 we have explored a novel variational optic flow methodology based on multi-scale feature points to extract cardiac motion from tagged MR images. Compared to constant brightness methods, this new approach exhibits several advantages. Although the intensity of critical points is also influenced by fading, critical points do retain their characteristic even in the presence of intensity changes, such as in MR imaging. In an experiment in section 5.4 we have applied this optic flow approach directly on tagged MR images. A visual inspection confirmed that the extracted motion fields realistically depicted the cardiac wall motion. The method exploits also the advantages from the multiscale framework. Because sparse velocity formulas 2.9, 3.7, 6.21, and 7.5 provide a number of equations equal to the number of unknowns, the method does not suffer from the aperture problem in retrieving velocities associated to the critical points. In chapters 2 and 3 we have moreover introduced a smoothness component of the optic flow equation described by means of covariant derivatives. This is a novelty in the optic flow literature. Many variational optic flow methods present a smoothness component that penalizes for changes from global assumptions such as isotropic or anisotropic smoothness. In the smoothness term proposed deviations from a predefined motion model are penalized. Moreover, the proposed optic flow equation has been decomposed in rotation-free and divergence-free components. This decomposition allows independent tuning of the two components during the vector field reconstruction. The experiments and the Table of errors provided in 3.8 showed that the combination of the smoothness term, influenced by a predefined motion model, and the Helmholtz decomposition in the optic flow equation reduces the average angular error substantially (20%-25%) with respect to a similar technique that employs only standard derivatives in the smoothness term. In section 5.3 we extracted the motion field of a phantom of which we know the ground truth of and compared the performance of this optic flow method with the performance of other optic flow methods well known in the literature, such as the Horn and Schunck [76] approach, the Lucas and Kanade [111] technique and the tuple image multi-scale optic flow constraint equation of Van Assen et al. [163]. Tests showed that the proposed optic flow methodology provides the smallest average angular error (AAE = 3.84 degrees) and L2 norm = 0.1. In this work we employed the Helmholtz decomposition also to study the cardiac behavior, since the vector field decomposition allows to investigate cardiac contraction and cardiac rotation independently. In chapter 4 we carried out an analysis of cardiac motion of ten volunteers and one patient where we estimated the kinetic energy for the different components. This decomposition is useful since it allows to visualize and quantify the contributions of each single vector field component to the heart beat. Local measurements of the kinetic energy have also been used to detect areas of the cardiac walls with little movement. Experiments on a patient and a comparison between a late enhancement cardiac image and an illustration of the cardiac kinetic energy on a bull’s eye plot illustrated that a correspondence between an infarcted area and an area with very small kinetic energy exists. With the aim to extend in the future the proposed optic flow equation to a 3D approach, in chapter 6 we investigated the 3D winding number approach as a tool to locate critical points in volume images. We simplified the mathematics involved with respect to a previous work [150] and we provided several examples and applications such as cardiac motion estimation from 3-dimensional tagged images, follicle and neuronal cell counting. Finally in chapter 7 we continued our investigation on volume tagged MR images, by retrieving the cardiac motion field using a 3-dimensional and simple version of the proposed optic flow equation based on standard derivatives. We showed that the retrieved motion fields display the contracting and rotating behavior of the cardiac muscle. We moreover extracted the through-plane component, which provides a realistic illustration of the vector field and is missed by 2-dimensional approaches

On the efficiency of stormwater detention tanks in pollutant removal

In the design of a stormwater detention tank is important to guarantee a sufficient retention time for the sedimentation of suspended solids, the biological uptake of nutrients and the die-off of bacteria carried in rainwaters. Long retention times increase the capacity of pollutant removal, but also the possibility of spills in downstream receivers and the risk of environmental pollution. In this paper, an analytical probabilistic approach, to estimate the probability distribution function of the average retention time and the efficiency in pollutant removal of stormwater tanks has been proposed. The possibility of water mixing from consecutive runoff events and storage carryover due to successive rainfall events has been considered. The method has been applied to a case study in Milano, Italy

A probabilistic approach to stormwater runoff control through permeable pavements beneath urban trees

: One of the most current and urgent challenges is making cities sustainable and resilient to climate change. From this perspective, Nature-Based Solutions (NBSs) are well-recognized strategies for stormwater control and water cycle restoration. Urban trees are an example of NBS. However, the high degree of soil sealing typically found in urban environments limits natural processes such as infiltration and hinders the water and nutrient supply for proper root development, which weakens tree stability. Permeable pavements at the base of urban trees, on the one hand, facilitate infiltration, which helps runoff control, and on the other hand, improve stormwater retention and soil humidity, which enhance root feeding. This paper proposes an analytical-probabilistic approach to estimate the contribution of permeable pavements to stormwater management. The equations developed in this study relate the runoff probability to the storage volume, the infiltration rate into the underlying soil, and the average values of the hydrological variables in the input. The model allows us to select different runoff thresholds and considers the possibility that residual volume from previous rainfall events prefills the storage capacity. An application to a case study in Sao Paulo (Brazil) has been presented. It investigates the influence of the different parameters used in the model on the results. The comparison of the outcomes obtained using the developed equations with those obtained from the continuous simulation of measured data confirmed the effectiveness of the proposed analytical-probabilistic approach and the suitability of using permeable pavements at the base of urban trees for improving stormwater retention

Rainwater Harvesting and Treatment: State of the Art and Perspectives

Rainwater harvesting is an ancient practice currently used for flood and drought risk mitigation. It is a well-known solution with different levels of advanced technology associated with it. This study is aimed at reviewing the state of the art with regards to rainwater harvesting, treatment, and management. It focuses on the environmental and social benefits of rainwater harvesting and links them to the Sustainable Development Goals. The review identifies characteristics of laws and regulations that encourage this practice and their current limitations. It presents methodologies to design a rainwater harvesting system, describes the influence of design variables, and the impact of temporal and spatial scales on the system's performance. The manuscript also analyzes the most advanced technologies for rainwater treatment, providing insights into various processes by discussing diverse physiochemical and biological technology options that are in the early stages of development. Finally, it introduces trends and perspectives which serve to increase rainwater harvesting, water reuse, and effective management

Prospecting movements link phenotypic traits to female annual potential fitness in a nocturnal predator.

Recent biologging technology reveals hidden life and breeding strategies of nocturnal animals. Combining animal movement patterns with individual characteristics and landscape features can uncover meaningful behaviours that directly influence fitness. Consequently, defining the proximate mechanisms and adaptive value of the identified behaviours is of paramount importance. Breeding female barn owls (Tyto alba), a colour-polymorphic species, recurrently visit other nest boxes at night. We described and quantified this behaviour for the first time, linking it with possible drivers, and individual fitness. We GPS-equipped 178 female barn owls and 122 male partners from 2016 to 2020 in western Switzerland during the chick rearing phase. We observed that 111 (65%) of the tracked breeding females were (re)visiting nest boxes while still carrying out their first brood. We modelled their prospecting parameters as a function of brood-, individual- and partner-related variables and found that female feather eumelanism predicted the emergence of prospecting behaviour (less melanic females are usually prospecting). More importantly we found that increasing male parental investment (e.g., feeding rate) increased female prospecting efforts. Ultimately, females would (re)visit a nest more often if they had used it in the past and were more likely to lay a second clutch afterwards, consequently having higher annual fecundity than non-prospecting females. Despite these apparent immediate benefits, they did not fledge more chicks. Through biologging and long-term field monitoring, we highlight how phenotypic traits (melanism and parental investment) can be related to movement patterns and the annual potential reproductive output (fecundity) of female barn owls

Cardiac motion estimation using multi-scale feature points

Heart illnesses influence the functioning of the cardiac muscle and are the major causes of death inthe world. Optic flow methods are essential tools to assess and quantify the contraction of the cardiacwalls, but are hampered by the aperture problem. Harmonic phase (HARP) techniques measure thephase in magnetic resonance (MR) tagged images. Due to the regular geometry, patterns generated bya combination of HARPs and sine HARPs represent a suitable framework to extract landmark features.In this paper we introduce a new aperture-problem free method to study the cardiac motion by trackingmulti-scale features such as maxima, minima, saddles and corners, on HARP and sine HARP taggedimages

Costs-benefit Analysis for the use of Shallow Groundwater as non-conventional Water Resource

Encouraging the implementation of non-conventional water resources (NCWR) is a fundamental strategy to face the future challenges due to urban population growth and resource scarcity. The implementation of a systematic process of Cost Benefit Analysis (CBA) offers reliable economic indicators to support decision makers in taking actions shifting towards NCWR. While infrastructure costs are directly estimated, while the benefits depend upon the considered stakeholders and require a tough estimation of the achieved ecosystem services. This research provides a framework for CBA analysis adopting NCWR at municipal level. The framework has been then applied to two case studies in Milan focused on the exploitation of shallow groundwater, where the obtained economic indicators has stressed out the importance of considering a complete benefits analysis that could support incentive policies on shifting part of the financial benefits to direct users leading to benefits for the whole community