Publications
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Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging
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Read more →: Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imagingModel-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data, the liver should be accurately segmented from the CT scans. Reconstructions of primary and model-based CBCT data need to be…
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Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging
•
Read more →: Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imagingModel-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data, the liver should be accurately segmented from the CT scans. Reconstructions of primary and model-based CBCT data need to be…
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Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging
•
Read more →: Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imagingModel-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data, the liver should be accurately segmented from the CT scans. Reconstructions of primary and model-based CBCT data need to be…
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Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging
•
Read more →: Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imagingModel-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data, the liver should be accurately segmented from the CT scans. Reconstructions of primary and model-based CBCT data need to be…
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Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging
•
Read more →: Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imagingModel-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data, the liver should be accurately segmented from the CT scans. Reconstructions of primary and model-based CBCT data need to be…
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Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging
•
Read more →: Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imagingModel-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data, the liver should be accurately segmented from the CT scans. Reconstructions of primary and model-based CBCT data need to be…
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Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging
•
Read more →: Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imagingModel-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data, the liver should be accurately segmented from the CT scans. Reconstructions of primary and model-based CBCT data need to be…
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Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging
•
Read more →: Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imagingModel-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data, the liver should be accurately segmented from the CT scans. Reconstructions of primary and model-based CBCT data need to be…
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Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging
•
Read more →: Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imagingModel-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data, the liver should be accurately segmented from the CT scans. Reconstructions of primary and model-based CBCT data need to be…
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Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging
•
Read more →: Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imagingModel-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT). To apply TST using prior knowledge extracted from CT perfusion data, the liver should be accurately segmented from the CT scans. Reconstructions of primary and model-based CBCT data need to be…