Unified adaptive framework for contrast enhancement of blood vessels

Information about blood vessel structures influences a lot of diseases in the medical realm. Therefore, for proper localization of blood vessels, its contrast should be enhanced properly. Since the blood vessels from all the medical angio-images have almost similar properties, a unified approach for the contrast enhancement of blood vessel structures is very useful. This paper aims to enhance the contrast of the blood vessels as well as the overall contrast of all the medical angio-images. In the proposed method, initially, the vessel probability map is extracted using hessian eigenanalysis. From the map, vessel edges and textures are derived and summed at every pixel location to frame a unique fractional differential function. The resulting fractional value from the function gives out the most optimal fractional order that can be adjusted to improve the contrast of blood vessels by convolving the image using Grunwald-Letnikov (G-L) fractional differential kernel. The vessel enhanced image is Gaussian fitted and contrast stretched to get overall contrast enhancement. This method of enhancement, when applied to medical angio-images such as the retinal fundus, Computerised Tomography (CT), Coronary Angiography (CA) and Digital Subtraction Angiography (DSA), has shown improved performance validated by the performance metrics

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

Acceleration of Subtractive Non-contrast-enhanced Magnetic Resonance Angiography

Although contrast-enhanced magnetic resonance angiography (CE-MRA) is widely established as a clinical examination for the diagnosis of human vascular diseases, non-contrast-enhanced MRA (NCE-MRA) techniques have drawn increasing attention in recent years. NCE-MRA is based on the intrinsic physical properties of blood and does not require the injection of any exogenous contrast agents. Subtractive NCE-MRA is a class of techniques that acquires two image sets with different vascular signal intensity, which are later subtracted to generate angiograms. The long acquisition time is an important drawback of NCE-MRA techniques, which not only limits the clinical acceptance of these techniques but also renders them sensitive to artefacts from patient motion. Another problem for subtractive NCE-MRA is the unwanted residual background signal caused by different static background signal levels on the two raw image sets. This thesis aims at improving subtractive NCE-MRA techniques by addressing both these limitations, with a particular focus on three-dimensional (3D) femoral artery fresh blood imaging (FBI). The structure of the thesis is as follows: Chapter 1 describes the anatomy and physiology of the vascular system, including the characteristics of arteries and veins, and the MR properties and flow characteristics of blood. These characteristics are the foundation of NCE-MRA technique development. Chapter 2 introduces commonly used diagnostic angiographic methods, particularly CE-MRA and NCE-MRA. Current NCE-MRA techniques are reviewed and categorised into different types. Their principles, implementations and limitations are summarised. Chapter 3 describes imaging acceleration theories including compressed sensing (CS), parallel imaging (PI) and partial Fourier (PF). The Split Bregman algorithm is described as an efficient CS reconstruction method. The SPIRiT reconstruction for PI and homodyne detection for PF are also introduced and combined with Split Bregman to form the basis of the reconstruction strategy for undersampled MR datasets. Four image quality metrics are presented for evaluating the quality of reconstructed images. In Chapter 4, an intensity correction method is proposed to improve background suppression for subtractive NCE-MRA techniques. Residual signals of background tissues are removed by performing a weighted subtraction, in which the weighting factor is obtained by a robust regression method. Image sparsity can also be increased and thereby potentially benefit CS reconstruction in the following chapters. Chapter 5 investigates the optimal k-space sampling patterns for the 3D accelerated femoral artery FBI sequence. A variable density Poisson-disk with a fully sampled centre region and missing partial Fourier fractions is employed for k-space undersampling in the ky-kz plane. Several key parameters in sampling pattern design, such as partial Fourier sampling ratios, fully sampled centre region size and density decay factor, are evaluated and optimised. Chapter 6 introduces several reconstruction strategies for accelerated subtractive NCE-MRA. A new reconstruction method, k-space subtraction with phase and intensity correction (KSPIC), is developed. By performing subtraction in k-space, KSPIC can exploit the sparsity of subtracted angiogram data and potentially improve the reconstruction performance. A phase correction procedure is used to restore the polarity of negative signals caused by subtraction. The intensity correction method proposed in Chapter 4 is also incorporated in KSPIC as it improves background suppression and thereby sparsity. The highly accelerated technique can be used not only to reduce the acquisition time, but also to enable imaging with increased resolution with no time penalty. A time-efficient high-resolution FBI technique is proposed in Chapter 7. By employing KSPIC and modifying the flow-compensation/spoiled gradients, the image matrix size can be increased from 256×256 to up to 512×512 without prolonging the acquisition time. Chapter 8 summarises the overall achievements and limitations of this thesis, as well as outlines potential future research directions.Cambridge Trust China Scholarship Council Addenbrooke’s Charitable Trust National Institute of Health Research, Cambridge Biomedical Research Cente

Fast catheter segmentation and tracking based on x-ray fluoroscopic and echocardiographic modalities for catheter-based cardiac minimally invasive interventions

X-ray fluoroscopy and echocardiography imaging (ultrasound, US) are two imaging modalities that are widely used in cardiac catheterization. For these modalities, a fast, accurate and stable algorithm for the detection and tracking of catheters is required to allow clinicians to observe the catheter location in real-time. Currently X-ray fluoroscopy is routinely used as the standard modality in catheter ablation interventions. However, it lacks the ability to visualize soft tissue and uses harmful radiation. US does not have these limitations but often contains acoustic artifacts and has a small field of view. These make the detection and tracking of the catheter in US very challenging. The first contribution in this thesis is a framework which combines Kalman filter and discrete optimization for multiple catheter segmentation and tracking in X-ray images. Kalman filter is used to identify the whole catheter from a single point detected on the catheter in the first frame of a sequence of x-ray images. An energy-based formulation is developed that can be used to track the catheters in the following frames. We also propose a discrete optimization for minimizing the energy function in each frame of the X-ray image sequence. Our approach is robust to tangential motion of the catheter and combines the tubular and salient feature measurements into a single robust and efficient framework. The second contribution is an algorithm for catheter extraction in 3D ultrasound images based on (a) the registration between the X-ray and ultrasound images and (b) the segmentation of the catheter in X-ray images. The search space for the catheter extraction in the ultrasound images is constrained to lie on or close to a curved surface in the ultrasound volume. The curved surface corresponds to the back-projection of the extracted catheter from the X-ray image to the ultrasound volume. Blob-like features are detected in the US images and organized in a graphical model. The extracted catheter is modelled as the optimal path in this graphical model. Both contributions allow the use of ultrasound imaging for the improved visualization of soft tissue. However, X-ray imaging is still required for each ultrasound frame and the amount of X-ray exposure has not been reduced. The final contribution in this thesis is a system that can track the catheter in ultrasound volumes automatically without the need for X-ray imaging during the tracking. Instead X-ray imaging is only required for the system initialization and for recovery from tracking failures. This allows a significant reduction in the amount of X-ray exposure for patient and clinicians.Open Acces

Computational methods for the analysis of functional 4D-CT chest images.

Medical imaging is an important emerging technology that has been intensively used in the last few decades for disease diagnosis and monitoring as well as for the assessment of treatment effectiveness. Medical images provide a very large amount of valuable information that is too huge to be exploited by radiologists and physicians. Therefore, the design of computer-aided diagnostic (CAD) system, which can be used as an assistive tool for the medical community, is of a great importance. This dissertation deals with the development of a complete CAD system for lung cancer patients, which remains the leading cause of cancer-related death in the USA. In 2014, there were approximately 224,210 new cases of lung cancer and 159,260 related deaths. The process begins with the detection of lung cancer which is detected through the diagnosis of lung nodules (a manifestation of lung cancer). These nodules are approximately spherical regions of primarily high density tissue that are visible in computed tomography (CT) images of the lung. The treatment of these lung cancer nodules is complex, nearly 70% of lung cancer patients require radiation therapy as part of their treatment. Radiation-induced lung injury is a limiting toxicity that may decrease cure rates and increase morbidity and mortality treatment. By finding ways to accurately detect, at early stage, and hence prevent lung injury, it will have significant positive consequences for lung cancer patients. The ultimate goal of this dissertation is to develop a clinically usable CAD system that can improve the sensitivity and specificity of early detection of radiation-induced lung injury based on the hypotheses that radiated lung tissues may get affected and suffer decrease of their functionality as a side effect of radiation therapy treatment. These hypotheses have been validated by demonstrating that automatic segmentation of the lung regions and registration of consecutive respiratory phases to estimate their elasticity, ventilation, and texture features to provide discriminatory descriptors that can be used for early detection of radiation-induced lung injury. The proposed methodologies will lead to novel indexes for distinguishing normal/healthy and injured lung tissues in clinical decision-making. To achieve this goal, a CAD system for accurate detection of radiation-induced lung injury that requires three basic components has been developed. These components are the lung fields segmentation, lung registration, and features extraction and tissue classification. This dissertation starts with an exploration of the available medical imaging modalities to present the importance of medical imaging in today’s clinical applications. Secondly, the methodologies, challenges, and limitations of recent CAD systems for lung cancer detection are covered. This is followed by introducing an accurate segmentation methodology of the lung parenchyma with the focus of pathological lungs to extract the volume of interest (VOI) to be analyzed for potential existence of lung injuries stemmed from the radiation therapy. After the segmentation of the VOI, a lung registration framework is introduced to perform a crucial and important step that ensures the co-alignment of the intra-patient scans. This step eliminates the effects of orientation differences, motion, breathing, heart beats, and differences in scanning parameters to be able to accurately extract the functionality features for the lung fields. The developed registration framework also helps in the evaluation and gated control of the radiotherapy through the motion estimation analysis before and after the therapy dose. Finally, the radiation-induced lung injury is introduced, which combines the previous two medical image processing and analysis steps with the features estimation and classification step. This framework estimates and combines both texture and functional features. The texture features are modeled using the novel 7th-order Markov Gibbs random field (MGRF) model that has the ability to accurately models the texture of healthy and injured lung tissues through simultaneously accounting for both vertical and horizontal relative dependencies between voxel-wise signals. While the functionality features calculations are based on the calculated deformation fields, obtained from the 4D-CT lung registration, that maps lung voxels between successive CT scans in the respiratory cycle. These functionality features describe the ventilation, the air flow rate, of the lung tissues using the Jacobian of the deformation field and the tissues’ elasticity using the strain components calculated from the gradient of the deformation field. Finally, these features are combined in the classification model to detect the injured parts of the lung at an early stage and enables an earlier intervention