Intelligent Interventional Ultrasound Fusion and Guidance

点击翻译按钮获取中文摘要

Image-guided surgeryusing ultrasound imaging requiresa surgeon to combine anatomical and pathological knowledge from preoperative imaging with real-time ultrasound images. This requires expert skills and experience.Computer-assisted navigation systems aim tostreamline the information fusion processby fusing the preoperative images with spatially-tracked ultrasound images.Traditional computational methods such as multimodal image registration facesignificant challenges incase-specificsurgical applications, whilst the recentartificial intelligence(AI) paradigm based on deep learningrequiresprohibitively large training sizefor interventional imagingdata.This project plans to apply deep neural networkswithin a new computational frameworkto develop a patient-specific surgical image registration system. The project willexplore a range of state-of-the-art machine learning methods including image synthesis,content-basedretrieval, domain adaptationand learning-based registration techniques, to develop anAI-enabledsurgical navigation system for laparoscopic liver resection.The clinical goal of this project is to dramatically improve status quosurgical navigation performance in automation and precision, using clinical dataeither already available or feasible to obtainfor training and validation.The student is expected tohave an aptitude for computationalmodellingand moderndeep learning methods and tools, proficiency in codingand medical image computing.