PET++: Improving Localisation, Diagnosis and Quantification in Clinical and Medical PET Imaging with Randomised Optimisation
PET++: Improving Localisation, Diagnosis and Quantification in Clinical and Medical PET Imaging with Randomised Optimisation
批准号:
EP/S026045/1
负责人:
Carola-Bibiane Schönlieb
金额:
$104.67万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --
中文摘要
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英文摘要
Positron Emission Tomography (PET) is a pillar of modern diagnostic imaging, allowing non-invasive, sensitive and specific detection of functional changes in several disease types. In endocrinology, the precise localisation of small functioning tumours of the pituitary or adrenal glands is crucial for planning curative surgery or radiotherapy. While PET imaging shows good promise for this task, initial studies suggest significant room for improvement, with improved PET imaging and subsequent more accurate localisation opening up the possibility for more adapted therapies. In dementia, the accurate quantification of PET images is key for the early detection of disease. Improved PET imaging may allow for earlier detection of dementia while asymptomatic and increased sensitivity to assess and monitor treatment once appropriate drugs have been found. In this project mathematicians team up with researchers and clinicians from Addenbrooke's Hospital Cambridge, Dementias Platform UK (DPUK), GE Healthcare and University College London (UCL) for improved diagnosis and localization for tumours in endocrinology and earlier diagnosis of dementia with improved PET imaging. In particular, we investigate modern PET reconstruction approaches based on advanced mathematical methods to increase the PET image resolution and contrast, while keeping computational complexity low, thereby directly benefiting clinical workflow.
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DOI:
10.1016/j.patcog.2021.108274
发表时间:
2022-03
期刊:
Pattern recognition
影响因子:
8
作者:
[Aviles-Rivero AI, Sellars P, Schönlieb CB, Papadakis N]
通讯作者:
Papadakis N
DOI:
10.1137/20m1357500
发表时间:
2017-12
期刊:
SIAM J. Imaging Sci.
影响因子:
--
作者:
[Martin Benning;M. Betcke;Matthias Joachim Ehrhardt;C. Schonlieb]
通讯作者:
Martin Benning;M. Betcke;Matthias Joachim Ehrhardt;C. Schonlieb
Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence.
通过人工智能中的隐私保护协作推进 COVID-19 诊断。
DOI:
10.17863/cam.79503
发表时间:
2021
期刊:
影响因子:
--
作者:
[Bai X]
通讯作者:
Bai X
DOI:
10.1017/s0962492919000059
发表时间:
2019-01-01
期刊:
ACTA NUMERICA
影响因子:
14.2
作者:
[Arridge, Simon, Maass, Peter, Schonlieb, Carola-Bibiane]
通讯作者:
Schonlieb, Carola-Bibiane
Research Exchanges in the Mathematics of Deep Learning with Applications
-
批准号:EP/Y037308/1
-
项目类别:Research Grant
-
资助金额:$24.32万
-
财政年份:2024
-
负责人:Carola-Bibiane Schönlieb
-
依托单位:
Combining Knowledge And Data Driven Approaches to Inverse Imaging Problems
-
批准号:EP/V029428/1
-
项目类别:Fellowship
-
资助金额:$158.04万
-
财政年份:2021
-
负责人:Carola-Bibiane Schönlieb
-
依托单位:
Cambridge Mathematics of Information in Healthcare (CMIH)
-
批准号:EP/T017961/1
-
项目类别:Research Grant
-
资助金额:$165.11万
-
财政年份:2020
-
负责人:Carola-Bibiane Schönlieb
-
依托单位:
Robust and Efficient Analysis Approaches of Remote Imagery for Assessing Population and Forest Health in India
-
批准号:EP/T003553/1
-
项目类别:Research Grant
-
资助金额:$70.41万
-
财政年份:2019
-
负责人:Carola-Bibiane Schönlieb
-
依托单位:
EPSRC Centre for Mathematical and Statistical Analysis of Multimodal Clinical Imaging
-
批准号:EP/N014588/1
-
项目类别:Research Grant
-
资助金额:$245.03万
-
财政年份:2016
-
负责人:Carola-Bibiane Schönlieb
-
依托单位:
Efficient computational tools for inverse imaging problems
-
批准号:EP/M00483X/1
-
项目类别:Research Grant
-
资助金额:$67.17万
-
财政年份:2014
-
负责人:Carola-Bibiane Schönlieb
-
依托单位:
Sparse & Higher Order Image Restoration
-
批准号:EP/J009539/1
-
项目类别:Research Grant
-
资助金额:$12.5万
-
财政年份:2012
-
负责人:Carola-Bibiane Schönlieb
-
依托单位:
国内基金
海外基金
Improving modelling of compact binary evolution.
-
批准号:10903001
-
项目类别:青年科学基金项目
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资助金额:20.0万元
-
批准年份:2009
-
负责人:史蒂芬
-
依托单位: