Imaging and registration for surgical guidance: systems and algorithms for intraoperative C-arm 2D and 3D imaging

medical imaging;image-guided surgery;image registration;computer-assisted interventions;x-ray imaging;intraoperative imaging;Computer Science

Uneri, AliPrince, Jerry L. ;

Johns Hopkins University

关键词: medical imaging;    image-guided surgery;    image registration;    computer-assisted interventions;    x-ray imaging;    intraoperative imaging;    Computer Science;   

Others  :  https://jscholarship.library.jhu.edu/bitstream/handle/1774.2/59314/uneri_dissertation.zip?sequence=2&isAllowed=y

瑞士|英语

来源: JOHNS HOPKINS DSpace Repository

【 摘 要 】

Advances in medical imaging, surgical navigation, and computing power over the past few decades have enabled the image guidance techniques that define the current state of the art in image-guided surgery. While modern navigation systems are an indispensable part of today’s surgical arsenal, they carry costs and workflow bottlenecks that have limited broad utilization. Originally conceptualized in the context of navigation relative to the preoperative data, among the most critical shortcomings is the assumption that the preoperative images accurately reflect the anatomy of the patient at the time of surgery. Intraoperative imaging offers the means to visualize such anatomical changes, as well as unexpected complications, and presents and important step to advancing the utility of image guidance across a broad spectrum of complex surgeries.Recognizing the potential of mobile C-arms capable of high-quality radiography, fluoroscopy, and cone-beam CT, this dissertation concerns the development of systems and algorithms to integrate C-arm imaging with other guidance technologies and present new methods to tackle current challenges in image guidance. The material includes work encompassing: (i) an extensible software platform for integrating navigational tools with cone-beam CT, including fast registration algorithms using parallel computation on general purpose GPU; (ii) a 3D-2D registration approach that leverages knowledge of interventional devices for surgical guidance and quality assurance; and (iii) a hybrid 3D deformable registration approach using image intensity and feature characteristics to resolve gross deformation in cone-beam CT guidance of thoracic surgery. Specific clinical challenges are presented, and the proposed solutions are subjected to rigorous quantitative evaluation to meet clinical requirements such as accuracy, precision, robustness, and computational efficiency (time constraints). The thesis realizes an image guidance framework that leverages the intraoperative imaging capabilities provided by modern C-arms and aims to show that their use, combined with advanced image registration algorithms, can overcome many of the limitations of conventional surgical navigation, streamline workflow, and enable novel applications in image-guided surgery.