EPSRC-NIHR HTC Partnership Award: Medical Image Analysis Network

EPSRC-NIHR HTC 合作伙伴奖：医学图像分析网络

• 批准号: EP/M000133/1
• 负责人: Alison Noble
• 金额: $ 19.31万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FM000133%2F1
• 关键词: EPSRC; NIHR; HTC; Partnership; Award

The EPSRC-NIHR Healthcare Technology Co-operatives Partnership Network in Medical Image Analysis seeks to bring leading UK researchers in medical image analysis together to identify new opportunities for medical image analysis methodology research within the clinical areas of high morbidity/unmet need of the NIHR Cardiovascular HTC and HTC in Colorectal Therapies.The HTCs are working with patient groups and clinicians on identifying unmet clinical needs in these areas. An aim of the new Medical Image Analysis Network is to bring together imaging scientists with different skills sets and experiences to consider how technological advances in how images are acquired and images (and associated information) are analysed can be applied to solve some of these problems. A purpose of the Network is to encourage new collaborations to be set up between academic healthcare technologists, clinicians and industry partners to develop and evaluate new solutions. We anticipate that Network members will jointly work on some of the hardest medical image analysis problems there are today. The hope is that the resulting research will lead to new image-based biomarkers which allow earlier detection of disease, better stratification of disease so that the most appropriate therapy can be selected for a patient, and new image-based quantitative tools to increase the success of interventions and therapies and improve the overall well-being of patients with these conditions.How will the Network achieve this goal? The Network will aim to encourage the development of new collaborations through workshops, joint meetings with other networks/organisations, small scale feasibility studies, Clinical Readiness events and Challenge competitions which will be open to the broader imaging research community. The hub for promotion of Network activities, dissemination of network outputs, and recruitment of new members (particularly from academia and industry not already involved in the HTCs) will be the Network website which will also act as an information source for imaging researchers interested in these clinical areas.

EPSRC-NIHR医疗技术合作伙伴关系网络在医学图像分析旨在将英国领先的医学图像分析研究人员聚集在一起，以确定在NIHR心血管HTC和结肠直肠治疗HTC的高发病率/未满足需求的临床领域内的医学图像分析方法研究的新机会。HTC正在与患者团体和临床医生合作，以确定这些领域未满足的临床需求。新的医学图像分析网络的一个目的是汇集具有不同技能和经验的成像科学家，以考虑如何获取图像和分析图像（及相关信息）的技术进步可以应用于解决其中一些问题。该网络的目的是鼓励学术医疗技术人员，临床医生和行业合作伙伴之间建立新的合作，以开发和评估新的解决方案。我们预计，网络成员将共同致力于解决当今最困难的医学图像分析问题。希望由此产生的研究将导致新的基于图像的生物标志物，允许早期检测疾病，更好的疾病分层，以便为患者选择最合适的治疗方法，以及新的基于图像的定量工具，以提高干预和治疗的成功率，并改善这些疾病患者的整体健康状况。网络将如何实现这一目标？该网络旨在鼓励通过研讨会，与其他网络/组织的联合会议，小规模可行性研究，临床准备活动和挑战赛（将向更广泛的成像研究界开放）开展新的合作。促进网络活动、传播网络成果和招募新成员（特别是来自尚未参与HTC的学术界和工业界）的中心将是网络网站，该网站也将作为对这些临床领域感兴趣的成像研究人员的信息来源。

项目成果

Repurposing of existing antibiotics for the treatment of diabetes mellitus.

重新利用现有抗生素来治疗糖尿病。

• DOI: 10.1007/978-3-319-17713-7_4
• 发表时间: 2022
• 期刊: In silico pharmacology
• 作者: Alam MS

In search of drugs to alleviate suppression of the host's innate immune responses against SARS-CoV-2 using a molecular modeling approach.

使用分子建模方法寻找药物来减轻宿主对 SARS-CoV-2 先天免疫反应的抑制。

• DOI: 10.1007/978-3-319-11698-3_26
• 发表时间: 2021
• 期刊: In silico pharmacology
• 作者: Choudhury S

Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III

医学图像计算和计算机辅助干预 - MICCAI 2015 - 第 18 届国际会议，德国慕尼黑，2015 年 10 月 5-9 日，会议记录，第 III 部分

• DOI: 10.1007/978-3-319-24574-4_69
• 发表时间: 2015
• 作者: Lindner C

Docking simulation and ADMET prediction based investigation on the phytochemical constituents of Noni (Morinda citrifolia) fruit as a potential anticancer drug.

基于对接模拟和 ADMET 预测的诺丽 (Morinda citrifolia) 果实作为潜在抗癌药物的植物化学成分的研究。

• DOI: 10.1007/978-3-662-44551-8_14
• 发表时间: 2022
• 期刊: In silico pharmacology
• 作者: Chandran K

Classification of amyloid status using machine learning with histograms of oriented 3D gradients.

• DOI: 10.1016/j.nicl.2016.05.004
• 发表时间: 2016
• 期刊: NeuroImage. Clinical
• 作者: Cattell L;Platsch G;Pfeiffer R;Declerck J;Schnabel JA;Hutton C;Alzheimer's Disease Neuroimaging Initiative
• 通讯作者: Alzheimer's Disease Neuroimaging Initiative