ArticleEJNMMI research2020
Regional SUV quantification in hybrid PET/MR, a comparison of two atlas-based automatic brain segmentation methods.
Article in EJNMMI research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Individualized diagnosis of Parkinson's disease based on multivariate magnetic resonance imaging radiomics and clinical indexes.Frontiers in aging neuroscience · 2025Article
- Identification of Parkinson's disease and multiple system atrophy using multimodal PET/MRI radiomics.European radiology · 2024Article
- Deep learning segmentation results in precise delineation of the putamen in multiple system atrophy.European radiology · 2023Article
- Article
- A Baboon Brain Atlas for Magnetic Resonance Imaging and Positron Emission Tomography Image Analysis.Frontiers in neuroanatomy · 2021Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundQuantitative analysis of brain positron-emission tomography (PET) depends on structural segmentation, which can be time-consuming and operator-dependent when performed manually. Previous automatic segmentation usually registered subjects' images onto an atlas template (defined as RSIAT here) for group analysis, which changed the individuals' images and probably affected regional PET segmentation. In contrast, we could register atlas template to subjects' images (RATSI), which created an individual atlas template and may be more accurate for PET segmentation. We segmented two representative brain areas in twenty Parkinson disease (PD) and eight multiple system atrophy (MSA) patients performed in hybrid positron-emission tomography/magnetic resonance imaging (PET/MR). The segmentation accuracy was evaluated using the Dice coefficient (DC) and Hausdorff distance (HD), and the standardized uptake value (SUV) measurements of these two automatic segmentation methods were compared, using manual segmentation as a reference.
resultsThe DC of RATSI increased, and the HD decreased significantly (P < 0.05) compared with the RSIAT in PD, while the results of one-way analysis of variance (ANOVA) found no significant differences in the SUV
conclusionThe RATSI was more accurate for the caudate nucleus and putamen automatic segmentation and can be used for regional PET analysis in hybrid PET/MR.
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