57 research outputs found
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels
Temporal point processes (TPP) are a natural tool for modeling event-based
data. Among all TPP models, Hawkes processes have proven to be the most widely
used, mainly due to their simplicity and computational ease when considering
exponential or non-parametric kernels. Although non-parametric kernels are an
option, such models require large datasets. While exponential kernels are more
data efficient and relevant for certain applications where events immediately
trigger more events, they are ill-suited for applications where latencies need
to be estimated, such as in neuroscience. This work aims to offer an efficient
solution to TPP inference using general parametric kernels with finite support.
The developed solution consists of a fast L2 gradient-based solver leveraging a
discretized version of the events. After supporting the use of discretization
theoretically, the statistical and computational efficiency of the novel
approach is demonstrated through various numerical experiments. Finally, the
effectiveness of the method is evaluated by modeling the occurrence of
stimuli-induced patterns from brain signals recorded with
magnetoencephalography (MEG). Given the use of general parametric kernels,
results show that the proposed approach leads to a more plausible estimation of
pattern latency compared to the state-of-the-art
Chemical kinetics modelling study on fuel autoignition in internal combustion engines
Chemical kinetics has been widely acknowledged as a fundamental theory in analysis of chemical processes and the corresponding reaction outputs and rates. The study and application of chemical kinetics thus provide a simulation tool to predict many characteristics a chemical process. Oxidation of hydrocarbon fuels applied in internal combustion engines is a complex chemical process involving a great number of a series of chained reaction steps and intermediate and simultaneous species. Symbolic and Numerical description of such a chemical process leads to the development and application of chemical kinetics models. The up-to-date application of chemical kinetics models is to the simulation of autoignition process in internal combustion engines.
Multi-zone thermodynamic combustion modelling has been regarded as a functional simulation approach to studying combustion process in IC engines as a decent compromise between computation accuracy and efficiency. Integration of chemical kinetics models into multi-zone models is therefore a potential modelling method to investigate the chemical and physical processes of autoignition in engine combustion.
This research work has been therefore concerned with the development, validation and application of multi-zone chemical kinetic engine models in the simulation of autoignition driven combustion in SI and HCCI engines. The contribution of this work is primarily made to establish a mathematical model based on the underlying physical and chemical principles of autoignition of the fuel-air mixture in SI and HCCI engines. Then, a computer code package has been developed to numerically solve the model. The derived model aims at improving the understanding of autoignition behaviour under engine-like conditions and providing an investigative tool to autoignition characteristics. Furthermore, as part of the ongoing program in the research of free piston engines, the results of this work will significantly aid in the investigation and simulation of the constant volume autoignition applied in free piston engines
Automatic Spatiotemporal Analysis of Cardiac Image Series
RÉSUMÉ
Ă€ ce jour, les maladies cardiovasculaires demeurent au premier rang des principales causes de
décès en Amérique du Nord. Chez l’adulte et au sein de populations de plus en plus jeunes,
la soi-disant épidémie d’obésité entraînée par certaines habitudes de vie tels que la mauvaise
alimentation, le manque d’exercice et le tabagisme est lourde de conséquences pour les personnes
affectées, mais aussi sur le système de santé. La principale cause de morbidité et de
mortalité chez ces patients est l’athérosclérose, une accumulation de plaque à l’intérieur des
vaisseaux sanguins à hautes pressions telles que les artères coronaires. Les lésions athérosclérotiques
peuvent entraîner l’ischémie en bloquant la circulation sanguine et/ou en provoquant
une thrombose. Cela mène souvent à de graves conséquences telles qu’un infarctus. Outre les
problèmes liés à la sténose, les parois artérielles des régions criblées de plaque augmentent la
rigidité des parois vasculaires, ce qui peut aggraver la condition du patient. Dans la population
pédiatrique, la pathologie cardiovasculaire acquise la plus fréquente est la maladie de
Kawasaki. Il s’agit d’une vasculite aigüe pouvant affecter l’intégrité structurale des parois des
artères coronaires et mener à la formation d’anévrismes. Dans certains cas, ceux-ci entravent
l’hémodynamie artérielle en engendrant une perfusion myocardique insuffisante et en activant
la formation de thromboses.
Le diagnostic de ces deux maladies coronariennes sont traditionnellement effectués à l’aide
d’angiographies par fluoroscopie. Pendant ces examens paracliniques, plusieurs centaines de
projections radiographiques sont acquises en séries suite à l’infusion artérielle d’un agent de
contraste. Ces images révèlent la lumière des vaisseaux sanguins et la présence de lésions
potentiellement pathologiques, s’il y a lieu. Parce que les séries acquises contiennent de l’information
très dynamique en termes de mouvement du patient volontaire et involontaire (ex.
battements cardiaques, respiration et déplacement d’organes), le clinicien base généralement
son interprétation sur une seule image angiographique où des mesures géométriques sont effectuées
manuellement ou semi-automatiquement par un technicien en radiologie. Bien que
l’angiographie par fluoroscopie soit fréquemment utilisé partout dans le monde et souvent
considéré comme l’outil de diagnostic “gold-standard” pour de nombreuses maladies vasculaires,
la nature bidimensionnelle de cette modalité d’imagerie est malheureusement très
limitante en termes de spécification géométrique des différentes régions pathologiques. En effet,
la structure tridimensionnelle des sténoses et des anévrismes ne peut pas être pleinement
appréciée en 2D car les caractéristiques observées varient selon la configuration angulaire de
l’imageur. De plus, la présence de lésions affectant les artères coronaires peut ne pas refléter
la véritable santé du myocarde, car des mécanismes compensatoires naturels (ex. vaisseaux----------ABSTRACT
Cardiovascular disease continues to be the leading cause of death in North America. In adult
and, alarmingly, ever younger populations, the so-called obesity epidemic largely driven by
lifestyle factors that include poor diet, lack of exercise and smoking, incurs enormous stresses
on the healthcare system. The primary cause of serious morbidity and mortality for these
patients is atherosclerosis, the build up of plaque inside high pressure vessels like the coronary
arteries. These lesions can lead to ischemic disease and may progress to precarious blood
flow blockage or thrombosis, often with infarction or other severe consequences. Besides
the stenosis-related outcomes, the arterial walls of plaque-ridden regions manifest increased
stiffness, which may exacerbate negative patient prognosis. In pediatric populations, the
most prevalent acquired cardiovascular pathology is Kawasaki disease. This acute vasculitis
may affect the structural integrity of coronary artery walls and progress to aneurysmal lesions.
These can hinder the blood flow’s hemodynamics, leading to inadequate downstream
perfusion, and may activate thrombus formation which may lead to precarious prognosis.
Diagnosing these two prominent coronary artery diseases is traditionally performed using
fluoroscopic angiography. Several hundred serial x-ray projections are acquired during selective
arterial infusion of a radiodense contrast agent, which reveals the vessels’ luminal
area and possible pathological lesions. The acquired series contain highly dynamic information
on voluntary and involuntary patient movement: respiration, organ displacement and
heartbeat, for example. Current clinical analysis is largely limited to a single angiographic
image where geometrical measures will be performed manually or semi-automatically by a
radiological technician. Although widely used around the world and generally considered
the gold-standard diagnosis tool for many vascular diseases, the two-dimensional nature of
this imaging modality is limiting in terms of specifying the geometry of various pathological
regions. Indeed, the 3D structures of stenotic or aneurysmal lesions may not be fully appreciated
in 2D because their observable features are dependent on the angular configuration of
the imaging gantry. Furthermore, the presence of lesions in the coronary arteries may not
reflect the true health of the myocardium, as natural compensatory mechanisms may obviate
the need for further intervention. In light of this, cardiac magnetic resonance perfusion
imaging is increasingly gaining attention and clinical implementation, as it offers a direct
assessment of myocardial tissue viability following infarction or suspected coronary artery
disease. This type of modality is plagued, however, by motion similar to that present in fluoroscopic
imaging. This issue predisposes clinicians to laborious manual intervention in order
to align anatomical structures in sequential perfusion frames, thus hindering automation o
Fast fully automatic myocardial segmentation in 4D cine cardiac magnetic resonance datasets
Dissertação de mestrado integrado em Engenharia BiomédicaCardiovascular diseases (CVDs) are the leading cause of death in the world, representing
30% of all global deaths. Among others, assessment of the left ventricular (LV) morphology and
global function using non-invasive cardiac imaging is an interesting technique for diagnosis and
treatment follow-up of patients with CVDs. Nowadays, cardiac magnetic resonance (CMR)
imaging is the gold-standard technique for the quantification of LV volumes, mass and ejection
fraction, requiring the delineation of endocardial and epicardial contours of the left ventricle from
cine MR images. In clinical practice, the physicians perform this segmentation manually, being a
tedious, time consuming and unpractical task. Even though several (semi-)automated methods
have been presented for LV CMR segmentation, fast, automatic and optimal boundaries
assessment is still lacking, usually requiring the physician to manually correct the contours.
In the present work, we propose a novel fast fully automatic 3D+time LV segmentation
framework for CMR datasets. The proposed framework presents three conceptual blocks: 1) an
automatic 2D mid-ventricular initialization and segmentation; 2) an automatic stack initialization
followed by a 3D segmentation at the end-diastolic phase; and 3) a tracking procedure to
delineate both endo and epicardial contours throughout the cardiac cycle. In each block, specific
CMR-targeted algorithms are proposed for the different steps required. Hereto, we propose
automatic and feasible initialization procedures. Moreover, we adapt the recent B-spline Explicit
Active Surfaces (BEAS) framework to the properties of CMR image segmentation by integrating
dedicated energy terms and making use of a cylindrical coordinate system that better fits the
topology of CMR data. At last, two tracking methods are presented and compared.
The proposed framework has been validated on 45 4D CMR datasets from a publicly
available database and on a large database from an ongoing multi-center clinical trial with 318
4D datasets. In the technical validation, the framework showed competitive results against the
state-of-the-art methods, presenting leading results in both accuracy and average computational
time in the common database used for comparative purposes. Moreover, the results in the large
scale clinical validation confirmed the high feasibility and robustness of the proposed framework
for accurate LV morphology and global function assessment. In combination with the low
computational burden of the method, the present methodology seems promising to be used in
daily clinical practice.As doenças cardiovasculares (DCVs) são a principal causa de morte no mundo,
representando 30% destas a nĂvel global. Na prática clĂnica, uma tĂ©cnica empregue no
diagnĂłstico de pacientes com DCVs Ă© a avaliação da morfologia e da função global do ventrĂculo
esquerdo (VE), através de técnicas de imagiologia não-invasivas. Atualmente, a ressonância
magnĂ©tica cardĂaca (RMC) Ă© a modalidade de referĂŞncia na quantificação dos volumes, massa e
fração de ejeção do VE, exigindo a delimitação dos contornos do endocárdio e epicárdio a partir
de imagens dinâmicas de RMC. Na prática clĂnica diária, o mĂ©todo preferencial Ă© a segmentação
manual. No entanto, esta é uma tarefa demorada, sujeita a erro humano e pouco prática. Apesar
de até à data diversos métodos (semi)-automáticos terem sido apresentados para a
segmentação do VE em imagens de RMC, ainda não existe um método capaz de avaliar
idealmente os contornos de uma forma automática, rápida e precisa, levando a que geralmente
o médico necessite de corrigir manualmente os contornos.
No presente trabalho é proposta uma nova framework para a segmentação automática
do VE em imagens 3D+tempo de RMC. O algoritmo apresenta trĂŞs blocos principais: 1) uma
inicialização e segmentação automática 2D num corte medial do ventrĂculo; 2) uma inicialização
e segmentação tridimensional no volume correspondente ao final da diástole; e 3) um algoritmo
de tracking para obter os contornos ao longo de todo o ciclo cardĂaco. Neste sentido, sĂŁo
propostos procedimentos de inicialização automática com elevada robustez. Mais ainda, é
proposta uma adaptação da recente framework “B-spline Explicit Active Surfaces” (BEAS) com a
integração de uma energia especĂfica para as imagens de RMC e utilizando uma formulação
cilĂndrica para tirar partido da topologia destas imagens. Por Ăşltimo, sĂŁo apresentados e
comparados dois algoritmos de tracking para a obtenção dos contornos ao longo do tempo.
A framework proposta foi validada em 45 datasets de RMC provenientes de uma base de
dados disponĂvel ao pĂşblico, bem como numa extensa base de dados com 318 datasets para
uma validação clĂnica. Na avaliação tĂ©cnica, a framework proposta obteve resultados
competitivos quando comparada com outros métodos do estado da arte, tendo alcançado
resultados de precisĂŁo e tempo computacional superiores a estes. Na validação clĂnica em larga
escala, a framework provou apresentar elevada viabilidade e robustez na avaliação da morfologia
e função global do VE. Em combinação com o baixo custo computacional do algoritmo, a
presente metodologia apresenta uma perspetiva promissora para a sua aplicação na prática
clĂnica diária
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