1,307 research outputs found
Optimized Adaptive Frangi-based Coronary Artery Segmentation using Genetic Algorithm
Diseases of coronary artery are deliberated as one of the most common heart diseases leading to death worldwide. For early detection of such disease, the X-ray angiography is a benchmark imaging modality for diagnosing such illness. The acquired X-ray angiography images usually suffer from low quality and the presence of noise. Therefore, for developing a computer-aided diagnosis (CAD) system, vessel enhancement and segmentation play significant role. In this paper, an optimized adapter filter based on Frangi filter was proposed for superior segmentation of the angiography images using genetic algorithm (GA). The original angiography image is initially preprocessed to enhance its contrast followed by generating the vesselness map using the proposed optimized Frangi filter. Then, a segmentation technique is applied to extract only the artery vessels, where the proposed system for extracting only the main vessel was evaluated. The experimental results on angiography images established the superiority of the vessel regions extraction showing 98.58% accuracy compared to the state-of-the-art
Computer integrated system: medical imaging & visualization
The intent of this book’s conception is to present research work using a user centered design approach. Due to space constraints, the story of the journey, included in this book is relatively brief. However we believe that it manages to adequately represent the story of the journey, from its humble beginnings in 2008 to the point where it visualizes future trends amongst both researchers and practitioners across the Computer Science and Medical disciplines.
This book aims not only to present a representative sampling of real-world collaboration between said disciplines but also to provide insights into the different aspects related to the use of real-world Computer Assisted Medical applications. Readers and potential clients should find the information particularly useful in analyzing the benefits of collaboration between these two fields, the products in and of their institutions.
The work discussed here is a compilation of the work of several PhD students under my supervision, who have since graduated and produced several publications either in journals or proceedings of conferences. As their work has been published, this book will be more focused on the research methodology based on medical technology used in their research. The research work presented in this book partially encompasses the work under the MOA for collaborative Research and Development in the field of Computer Assisted Surgery and Diagnostics pertaining to Thoracic and Cardiovascular Diseases between UPM, UKM and IJN, spanning five years beginning from 15 Feb 2013
Automatic Spatiotemporal Analysis of Cardiac Image Series
RÉSUMÉ
À 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
Automatic Spatiotemporal Analysis of Cardiac Image Series
RÉSUMÉ
À 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
Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 156)
This bibliography lists 170 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1976
Accurate Segmentation of Cerebrovasculature from TOF-MRA Images Using Appearance Descriptors
© 2013 IEEE. Analyzing cerebrovascular changes can significantly lead to not only detecting the presence of serious diseases e.g., hypertension and dementia, but also tracking their progress. Such analysis could be better performed using Time-of-Flight Magnetic Resonance Angiography (ToF-MRA) images, but this requires accurate segmentation of the cerebral vasculature from the surroundings. To achieve this goal, we propose a fully automated cerebral vasculature segmentation approach based on extracting both prior and current appearance features that have the ability to capture the appearance of macro and micro-vessels in ToF-MRA. The appearance prior is modeled with a novel translation and rotation invariant Markov-Gibbs Random Field (MGRF) of voxel intensities with pairwise interaction analytically identified from a set of training data sets. The appearance of the cerebral vasculature is also represented with a marginal probability distribution of voxel intensities by using a Linear Combination of Discrete Gaussians (LCDG) that its parameters are estimated by using a modified Expectation-Maximization (EM) algorithm. The extracted appearance features are separable and can be classified by any classifier, as demonstrated by our segmentation results. To validate the accuracy of our algorithm, we tested the proposed approach on in-vivo data using 270 data sets, which were qualitatively validated by a neuroradiology expert. The results were quantitatively validated using the three commonly used metrics for segmentation evaluation: the Dice coefficient, the modified Hausdorff distance, and the absolute volume difference. The proposed approach showed a higher accuracy compared to two of the existing segmentation approaches
The computation of blood flow waveforms from digital X-ray angiographic data
This thesis investigates a novel technique for the quantitative measurement of pulsatile blood flow waveforms and mean blood flow rates using digital X-ray angiographic data. Blood flow waveforms were determined following an intra-arterial injection of contrast material. Instantaneous blood velocities were estimated by generating a 'parametric image' from dynamic X-ray angiographic images in which the image grey-level represented contrast material concentration as a function of time and true distance in three dimensions along a vessel segment. Adjacent concentration-distance profiles in the parametric image of iodine concentration versus distance and time were shifted along the vessel axis until a match occurred. A match was defined as the point where the mean sum of the squares of the differences between the two profiles was a minimum. The distance translated per frame interval gave the instantaneous contrast material bolus velocity. The technique initially was validated using synthetic data from a computer simulation of angiographic data which included the effect of pulsatile blood flow and X-ray quantum noise. The data were generated for a range of vessels from 2 mm to 6 mm in diameter. Different injection techniques and their effects on the accuracy of blood flow measurements were studied. Validation of the technique was performed using an experimental phantom of blood circulation, consisting of a pump, flexible plastic tubing, the tubular probe of an electromagnetic flowmeter and a solenoid to simulate a pulsatile flow waveform which included reverse flow. The technique was validated for both two- and three-dimensional representations of the blood vessel, for various flow rates and calibre sizes. The effects of various physical factors were studied, including the distance between injection and imaging sites and the length of artery analysed. Finally, this method was applied to clinical data from femoral arteries and arteries in the head and neck
3D reconstruction of coronary arteries from angiographic sequences for interventional assistance
Introduction -- Review of literature -- Research hypothesis and objectives -- Methodology -- Results and discussion -- Conclusion and future perspectives
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