A graph-theoretic variational segmentation algorithm is applied to 22-frame dynamic positron emission tomography (PET) data sets after dimension reduction along ...
A graph-theoretic variational segmentation algorithm is applied to 22-frame dynamic positron emission tomography (PET) data sets after dimension reduction ...
Results indicate that the PCA is a very useful initial preprocessing step for segmentation and is effective in minimising the artifacts present in the PET ...
A graph-theoretic variational segmentation algorithm is applied to 22-frame dynamic positron emission tomography (PET) data sets after dimension reduction ...
Oct 22, 2024 · PCA has been investigated in the context of variational image segmentation before, both as a means for dimension reduction [26] and to increase ...
We combined k-means with two different preprocessing approaches, namely, principal component analysis (PCA) and independent component analysis (ICA). Then, we ...
Dec 5, 2023 · Clustering time activity curves of PET images have been used to separate clinically relevant areas of the brain or tumours.
We have used PCA, ICA and SM techniques and applied them to dynamic 2-deoxy-2 [18F]fluoro-D-glucose (18F-FDG) PET studies, first to realistic synthetic data ...
Missing: Variational | Show results with:Variational
A PCA of the original dynamic PET data is used to reduce the data set to the significant informa- tion. Step 2: The PCA channels are segmented using an en-.
This paper introduces a novel variational segmentation method within the fuzzy framework, which solves the problem of segmenting multi-region color-scale ...