Parallel Computation of Nonrigid Image Registration

Automatic intensity-based nonrigid image registration brings significant impact in medical applications such as multimodality fusion of images, serial comparison for monitoring disease progression or regression, and minimally invasive image-guided interventions. However, due to memory and compute intensive nature of the operations, intensity-based image registration has remained too slow to be practical for clinical adoption, with its use limited primarily to as a pre-operative too. Efficient registration methods can lead to new possibilities for development of improved and interactive intraoperative tools and capabilities. In this thesis, we propose an efficient parallel implementation for intensity-based three-dimensional nonrigid image registration on a commodity graphics processing unit. Optimization techniques are developed to accelerate the compute-intensive mutual information computation. The study is performed on the hierarchical volume subdivision-based algorithm, which is inherently faster than other nonrigid registration algorithms and structurally well-suited for data-parallel computation platforms. The proposed implementation achieves more than 50-fold runtime improvement over a standard implementation on a CPU. The execution time of nonrigid image registration is reduced from hours to minutes while retaining the same level of registration accuracy

Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery

Intraoperative brain shift during neurosurgical procedures is a well-known phenomenon caused by gravity, tissue manipulation, tumor size, loss of cerebrospinal fluid (CSF), and use of medication. For the use of image-guided systems, this phenomenon greatly affects the accuracy of the guidance. During the last several decades, researchers have investigated how to overcome this problem. The purpose of this paper is to present a review of publications concerning different aspects of intraoperative brain shift especially in a tumor resection surgery such as intraoperative imaging systems, quantification, measurement, modeling, and registration techniques. Clinical experience of using intraoperative imaging modalities, details about registration, and modeling methods in connection with brain shift in tumor resection surgery are the focuses of this review. In total, 126 papers regarding this topic are analyzed in a comprehensive summary and are categorized according to fourteen criteria. The result of the categorization is presented in an interactive web tool. The consequences from the categorization and trends in the future are discussed at the end of this work

Sistema multimodal para medir el desplazamiento cerebral intraoperatorio en tiempo real

Programa de Doctorado en Tecnologías Industriales y de TelecomunicaciónLa neurocirugía robótica está sufriendo profundos cambios en los últimos tiempos, fruto principalmente de los avances en las técnicas de imagen médica (TAC, RM, RMf o DTI), lo que permite una mejor planificación de la operación a realizar. La neurocirugía mínimamente invasiva se ve beneficiada de estos avances. Sin embargo, quedan problemas a resolver en la transferencia del plan de trabajo preplanificado a la realidad intraoperatoria, debido a la naturaleza no lineal de los tejidos deformables involucrados. Uno de estos problemas es el brain shift, o desplazamiento de la materia cerebral producto del cambio de presión interior al practicar la craneotomía y de los propios procesos quirúrgicos, que producen una pérdida de referencia de los volúmenes de imagen de neurocirugía adquiridos antes de la cirugía. Los quirófanos con RM intraoperatoria han demostrado ser muy caros, y por tanto, poco accesibles para solucionar este problema de pérdida de referencia. Este trabajo de tesis doctoral presenta el desarrollo de un sistema colaborativo intraoperatorio de RA en técnicas de neurocirugía mínimamente invasiva. En concreto, permite visualizar en hologramas 3D el modelo cerebral del paciente con todas las deformaciones que van ocurriendo durante la neurocirugía, en base a la información en tiempo real proporcionada por un nuevo sistema para la medición de distancias de manera no invasiva. Las deformaciones volumétricas sufridas en puntos no visibles del cerebro son obtenidas mediante un conjunto de antenas de microondas y un modelo matemático biomecánico. El aporte de esta tesis doctoral ha sido, por tanto, generar una herramienta para la neurocirugía robótica que permita ayudar a solucionar los actuales problemas de localización derivados del fenómeno del brain shift