Using AI to enable imaging of exotic radionuclides for Molecular Radiotherapy
Using AI to enable imaging of exotic radionuclides for Molecular Radiotherapy
批准号:
2874500
负责人:
金额:
$0.0万
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
点击翻译按钮获取中文摘要
英文摘要
1) Brief description of the context of the research including potential impactMolecular Radiotherapy (MRT) is a rapidly growing cancer treatment modality where molecules that bind to cancerous cells are labelled with a radionuclide and injected into the patient for targeted delivery of radiation. Multimodality imaging using CT and nuclear imaging (SPECT/PET) can be performed to personalise the treatment doses as well as quantify absorbed doses to the tumours and organs at risk (OAR). There is increased interest in the use of exotic radionuclides including alpha-emitters such as Actinium-225 that have the potential to increase dose to the tumours while minimising impact on OARs, especially when combined with novel molecules that specifically target receptors or proteins in the tumours. 2) Aims and ObjectivesThe aim is to develop novel image reconstruction methods to enable quantitative imaging of exotic radionuclides with low levels of gamma emissions, focusing on alpha-emitters such as Actinium-225. The approach will integrate physics-based machine learning methods into the reconstruction process, combining the use of advanced modelling of the imaging physics, data from planning scans with state-of-the-art Deep Learning. Optimisation of acquisition protocols will be investigated. Test data will include Monte Carlo simulations, phantom scans (acquired as part of this project) as well as potentially patient data obtained as part of a clinical trial.3) Novelty of Research Methodology Imaging these novel radionuclides is very challenging due to their low abundance of generated gamma photons. Machine learning techniques are revolutionising the field of image reconstruction in general, and for ultra-low signal data in particular.4) Alignment to EPSRC's strategies and research areasThis project is aligned with the EPSRC strategy on "discovering and accelerating the development of new interventions" and "improving population health" by optimising imaging and dosimetry for theranostics using MRT.5) Any companies or collaborators involvedBlue Earth Therapeutics LtdNational Physical Laboratory (NPL)
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
国内基金
海外基金
登录
查看更多内容
基于协同创新视角下AI赋能课程体系的模块化开发与应用研究
-
批准号:
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2026
-
负责人:吴惠玲
-
依托单位:
基于AI驱动的教育教学平台系统的开发与应用
-
批准号:
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2026
-
负责人:曹琪敏
-
依托单位:
基于AI智链驱动的跨境电商平台系统开发
-
批准号:
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2026
-
负责人:蔡永林
-
依托单位:
AI赋能未成年人心理健康应用研究
-
批准号:
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2026
-
负责人:傅绪荣
-
依托单位:
备多分AI智能研学系统开发
-
批准号:
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2026
-
负责人:常直杨
-
依托单位:
AI智慧体育操场的设计与应用
-
批准号:
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2026
-
负责人:王斌
-
依托单位:
长沙软件园 “轻量化AI大模型矩阵 ”科技型企业孵化器建设
-
批准号:2026ZYT011
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2026
-
负责人:方永强
-
依托单位:
面向AI驱动的信息化工程监管与自动化测试平台研发
-
批准号:
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2026
-
负责人:刘登志
-
依托单位:
建筑-音乐跨模态AI生成平台研发与应用
-
批准号:
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2026
-
负责人:许蕴彰
-
依托单位:
适用于AI眼镜的横向错位光学变焦系统技术开发
-
批准号:
-
项目类别:省市级项目
-
资助金额:--
-
批准年份:2026
-
负责人:窦健泰
-
依托单位: