Development of Artificial Intelligence tools for therapeutic ultrasound

该项目将包括研究将AI/ML应用于声学系统所需的初步步骤。在初步调查之后（可能作为夏季项目的一部分），可以对项目的前进方向做出决定。预计整个项目将提供一系列AI/ML工具，每个建筑都在最后一个建筑上，这将提高声学系统的性能。现有数据集可用于其中一些任务，而acoustic将与FUSE合作，为其他任务开发必要的数据集，并提供额外的数据集来增强现有的数据集。计划的开发任务，可以构成这个项目，可能包括：1)融合下一代系统的MR和US图像，并使用融合的图像来提高对组织材料特性的认识2)使用ML来改善超声通过畸变组织的聚焦，以确保健康组织不受损；3)使用ML计算治疗脉冲的热效应，用于实时治疗监测4)使用ML进行目标区域的运动跟踪，以消除治疗中呼吸引起的错误对安全有效的USgFUS的要求是广泛的，并且在该领域有许多正在进行的工作机会。

This project would involve looking at what preliminary steps would be required to apply AI/ML to the Acoustiic system. After this initial investigation, potentially done as part of the summer project, a decision can be made on the forward direction of the project. It is envisioned that the overall project will provide a series of AI/ML tools, each building on the last, that will improve the performance of the Acoustiic system. There are existing data sets available for some of these tasks, while Acoustiic would work with FUSE to develop necessary datasets for others, and additional datasets to enhance existing. Planned development tasks, that could make up this project, could include:1) Fusion of MR and US images for next generation system, and use of fused images to improve knowledge of material properties of tissue2) Use of ML to improve focusing of ultrasound through aberrating tissue to ensure healthy tissue is not damaged, with the fastest destruction of tumours3) Use of ML to calculate thermal effects of therapeutic pulses for real-time therapy monitoring4) Use of ML for motion tracking of target regions, to remove breathing induced errors in therapyThe requirements for safe, effective USgFUS are extensive and there are many opportunities for ongoing work in this area.