This methodology can be used for pre-treatment dosimetry and for SIRT planning including the determination of the activity that should be administered to achieve the therapeutical goal. The results showed disagreement between lobe segmentation using CBCT images compared to lobe segmentation based on CT images (average Hausdorff distance of 14.18 mm), with a high impact on the dosimetry (differences up to 9 Gy for right and 21 Gy for the left liver lobe). The semi-automatic liver segmentation agreed well with manual liver segmentation (dice coefficient of 0.92 and an average Hausdorff distance of 3.04 mm). The image registration performs well according to the expert reviewer (scored as perfect or with little misalignment in 94% of the cases). The results for image registration showed acceptable alignment with limited impact on dosimetry. Our methodology showed that multi-modal image analysis can be used for determination of the liver and perfusion territories using CBCT in SIRT using all pre-treatment studies. The segmentations of the liver and liver lobes were compared to the manual segmentations by an expert on a CT image. The total liver was segmented semi-automatically based on the PET/CT and SPECT/CT images, and the liver perfusion territories were determined based on the CBCT images. The registration was scored by an expert using Likert scores. The pre-treatment 18F-FDG PET/CT, 99mTc-MAA SPECT/CT, and contrast-enhanced CBCT images were registered to a common space using an initial rigid, followed by a deformable registration. In this paper, we proposed a procedure for multi-modal image analysis to assist SIRT treatment planning. For radiation dose prediction calculations, a segmentation of the total liver volume and of the liver perfusion territories is required. Art history and other cultural studies can finally realise the potential of the network based and collaborative analysis of images.We have developed a multi-modal imaging approach for SIRT, combining 99mTc-MAA SPECT/CT and/or 90Y PET, 18F-FDG PET/CT, and contrast-enhanced CBCT for voxel-based dosimetry, as a tool for treatment planning and verification. This synthesis creates the ability to reorganise, juxtapose and annotate images in a way that can lead to new conclusions concerning image-based research. It allows the identification of motifs, the creation of linked image networks as well as the addition of metadata. This image annotation tool serves as an instrument to support research in art history. The numerous users, the secure legal context for use and the existing technologies for collaborative research make prometheus a perfect subject for HyperImage. prometheus provides over 700,000 images in nearly 60 connected image databases Hyperimage facilitates collaborative work directly on the image. Meta-Image combines the distributed digital image archive prometheus, which consists of a very large pool of images, with HyperImage (), a tool for image annotation. It consists of the two components prometheus and HyperImage. The aim of the project Meta-Image, funded by German Research Foundation (DFG), is to provide a networkbased research environment for art history and other sciences concerning visual culture. Collaborative research, visual culture, art history, image-based research, network-based research, image database, Aby Warburg, linking, annotations.
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