Coronary Artery Segmentation and Motion Modelling

Conventional coronary artery bypass surgery requires invasive sternotomy and the use of a cardiopulmonary bypass, which leads to long recovery period and has high infectious potential. Totally endoscopic coronary artery bypass (TECAB) surgery based on image guided robotic surgical approaches have been developed to allow the clinicians to conduct the bypass surgery off-pump with only three pin holes incisions in the chest cavity, through which two robotic arms and one stereo endoscopic camera are inserted. However, the restricted field of view of the stereo endoscopic images leads to possible vessel misidentification and coronary artery mis-localization. This results in 20-30% conversion rates from TECAB surgery to the conventional approach. We have constructed patient-specific 3D + time coronary artery and left ventricle motion models from preoperative 4D Computed Tomography Angiography (CTA) scans. Through temporally and spatially aligning this model with the intraoperative endoscopic views of the patient's beating heart, this work assists the surgeon to identify and locate the correct coronaries during the TECAB precedures. Thus this work has the prospect of reducing the conversion rate from TECAB to conventional coronary bypass procedures. This thesis mainly focus on designing segmentation and motion tracking methods of the coronary arteries in order to build pre-operative patient-specific motion models. Various vessel centreline extraction and lumen segmentation algorithms are presented, including intensity based approaches, geometric model matching method and morphology-based method. A probabilistic atlas of the coronary arteries is formed from a group of subjects to facilitate the vascular segmentation and registration procedures. Non-rigid registration framework based on a free-form deformation model and multi-level multi-channel large deformation diffeomorphic metric mapping are proposed to track the coronary motion. The methods are applied to 4D CTA images acquired from various groups of patients and quantitatively evaluated

Upper airways segmentation using principal curvatures

Esta tesis propone una nueva técnica para segmentar las vías aéreas superiores. Esta propuesta permite la extracción de estructuras curvilíneas usando curvaturas principales. La propuesta permite la extracción de éstas estructuras en imágenes 2D y 3D. Entre las principales novedades se encuentra la propuesta de un nuevo criterio de parada en la propagación del algoritmo de realce de contraste (operador multi-escala de tipo sombrero alto). De la misma forma, el criterio de parada propuesto es usado para detener los algoritmos de difusión anisotrópica. Además, un nuevo criterio es propuesto para seleccionar las curvaturas principales que conforman las estructuras curvilíneas, que se basa en los criterios propuestos por Steger, Deng et. al. y Armande et. al. Además, se propone un nuevo algoritmo para realizar la supresión de nomáximos que permite reducir la presencia de discontinuidades en el borde de las estructuras curvilíneas. Para extraer los bordes de las estructuras curvilíneas, se utiliza un algoritmo de enlace que incluye un nuevo criterio de distancia para reducir la aparición de agujeros en la estructura final. Finalmente, con base en los resultados obtenidos, se utiliza un algoritmo morfológico para cerrar los agujeros y se aplica un algoritmo de crecimiento de regiones para obtener la segmentación final de las vías respiratorias superiores.This dissertation proposes a new approach to segment the upper airways. This proposal allows the extraction of curvilinear structures based on the principal curvatures. The proposal allows extracting these structures from 2D and 3D images. Among the main novelties is the proposal of a new stopping criterion to stop the propagation of the contrast enhancement algorithm (multiscale top-hat morphological operator). In the same way, the proposed stopping criterion is used to stop the anisotropic diffusion algorithms. In addition, a new criterion is proposed to select the principal curvatures that make up the curvilinear structures, which is based on the criteria proposed by Steger, Deng et. al. and Armande et. al. Furthermore, a new algorithm to perform the non-maximum suppression that allows reducing the presence of discontinuities in the border of curvilinear structures is proposed. To extract the edges of the curvilinear structures, a linking algorithm is used that includes a new distance criterion to reduce the appearance of gaps in the final structure. Finally, based on the obtained results, a morphological algorithm is used to close the gaps and a region growing algorithm to obtain the final upper airways segmentation is applied.Doctor en IngenieríaDoctorad

Handbook of Vascular Biometrics

This open access handbook provides the first comprehensive overview of biometrics exploiting the shape of human blood vessels for biometric recognition, i.e. vascular biometrics, including finger vein recognition, hand/palm vein recognition, retina recognition, and sclera recognition. After an introductory chapter summarizing the state of the art in and availability of commercial systems and open datasets/open source software, individual chapters focus on specific aspects of one of the biometric modalities, including questions of usability, security, and privacy. The book features contributions from both academia and major industrial manufacturers

Caracterización del Edema Macular Diabético mediante análisis automático de Tomografías de Coherencia Óptica

Programa Oficial de Doctorado en Computación. 5009V01[Abstract] Diabetic Macular Edema (DME) is one of the most important complications of diabetes and a leading cause of preventable blindness in the developed countries. Among the di erent image modalities, Optical Coherence Tomography (OCT) is a non-invasive, cross-sectional and high-resolution imaging technique that is commonly used for the analysis and interpretation of many retinal structures and ocular disorders. In this way, the development of Computer-Aided Diagnosis (CAD) systems has become relevant over the recent years, facilitating and simplifying the work of the clinical specialists in many relevant diagnostic processes, replacing manual procedures that are tedious and highly time-consuming. This thesis proposes a complete methodology for the identi cation and characterization of DMEs using OCT images. To do so, the system combines and exploits di erent clinical knowledge with image processing and machine learning strategies. This automatic system is able to identify and characterize the main retinal structures and several pathological conditions that are associated with the DME disease, following the clinical classi cation of reference in the ophthalmological eld. Despite the complexity and heterogeneity of this relevant ocular pathology, the proposed system achieved satisfactory results, proving to be robust enough to be used in the daily clinical practice, helping the clinicians to produce a more accurate diagnosis and indicate adequate treatments[Resumen] El Edema Macular Diabético (EMD) es una de las complicaciones más importantes de la diabetes y una de las principales causas de ceguera prevenible en los países desarrollados. Entre las diferentes modalidades de imagen, la Tomografía de Coherencia Óptica (TCO) es una técnica de imagen no invasiva, transversal y de alta resolución que se usa comúnmente para el análisis e interpretación de múltiples estructuras retinianas y trastornos oculares. De esta manera, el desarrollo de los sistemas de Diagnóstico Asistido por Ordenador (DAO) se ha vuelto relevante en los últimos años, facilitando y simplificando el trabajo de los especialistas clínicos en muchos procesos diagnósticos relevantes, reemplazando procedimientos manuales que son tediosos y requieren mucho tiempo. Esta tesis propone una metodología completa para la identificación y caracterización de EMDs utilizando imágenes TCO. Para ello, el sistema desarrollado combina y explota diferentes conocimientos clínicos con estrategias de procesamiento de imágenes y aprendizaje automático. Este sistema automático es capaz de identificar y caracterizar las principales estructuras retinianas y diferentes afecciones patológicas asociadas con el EMD, siguiendo la clasificación clínica de referencia en el campo oftalmológico. A pesar de la complejidad de esta relevante patología ocular, el sistema propuesto logró resultados satisfactorios, demostrando ser lo sufi cientemente robusto como para ser usado en la práctica clínica diaria, ayudando a los médicos a producir diagnósticos más precisos y tratamientos más adecuados.[Resumo] O Edema Macular Diabético ( EMD) é unha das complicacións máis importantes da diabetes e unha das principais causas de cegueira prevenible nos países desenvoltos. Entre as diferentes modalidades de imaxe, a Tomografía de Coherencia Óptica ( TCO) é unha técnica de imaxe non invasiva, transversal e de alta resolución que se usa comunmente para a análise e interpretación de múltiples estruturas retinianas e trastornos oculares. Desta maneira, o desenvolvemento dos sistemas de Diagnóstico Asistido por Computador ( DAO) volveuse relevante nos últimos anos, facilitando e simplificando o traballo dos especialistas clínicos en moitos procesos diagnósticos relevantes, substituíndo procedementos manuais que son tediosos e requiren moito tempo. Esta tese propón unha metodoloxía completa para a identificación e caracterización de EMDs utilizando imaxes TCO. Para iso, o sistema desenvolto combina e explota diferentes coñecementos clínicos con estratexias de procesamento de imaxes e aprendizaxe automático. Este sistema automático é capaz de identificar e caracterizar as principais estruturas retinianas e diferentes afeccións patolóxicas asociadas co EMD, seguindo a clasificación clínica de referencia no campo oftalmolóxico. A pesar da complexidade desta relevante patoloxía ocular, o sistema proposto logrou resultados satisfactorios, demostrando ser o sufi cientemente robusto como para ser usado na práctica clínica diaria, axudando aos médicos para producir diagnósticos máis precisos e tratamentos máis adecuados

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