Automated segmentation and quantification of geometrical and structural parameters of the hip in 3D-MRI data sets: Development of algorithms for reliable data analysis in large cohorts (German National Cohort)
Automated segmentation and quantification of geometrical and structural parameters of the hip in 3D-MRI data sets: Development of algorithms for reliable data analysis in large cohorts (German National Cohort)
批准号:
325028047
负责人:
Professor Dr. Mike Notohamiprodjo
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2017
资助国家:
德国
项目状态:
已结题
起止时间:
2016-12-31 至 2019-12-31
中文摘要
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英文摘要
Standardized and validated tools with a high degree of automatization are required for the assessment of the MRI-data of the approximately 30,000 participants of the German National Cohort (GNC) imaging sub-study. The purpose of this project is to develop and test software algorithms for automated segmentation of the hip joint exploiting the pelvis sequences of 200 exemplary MRI datasets provided by the GNC. The software algorithms will automatically quantify the following imaging parameters: Acetabular coverage, sphericity of the femoral head, offset femoral head/neck, proximal femoral form, cartilage area and thickness, acetabular and femoral cysts. These automatically derived parameters will be compared to manual analysis and validated in a separate clinically correlated patient cohort. Finally, the developed software tools will allow for automated quantitative assessment of structural changes which may predispose individuals to develop hip osteoarthritis.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1109/icip.2018.8451205
发表时间:
2018-10
期刊:
2018 25th IEEE International Conference on Image Processing (ICIP)
影响因子:
--
作者:
[T. Küstner;Sarah Müller;Marc Fischer;Jakob Weiss;K. Nikolaou;F. Bamberg;Bin Yang;F. Schick;S. Gatidis]
通讯作者:
T. Küstner;Sarah Müller;Marc Fischer;Jakob Weiss;K. Nikolaou;F. Bamberg;Bin Yang;F. Schick;S. Gatidis
海外基金