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
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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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Free-breathing 3D Stack-of-Stars Gradient Echo Sequence in MR-guided Percutaneous Liver Interventions: Evaluation of Workflow and Diagnostic Quality
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Read more →: Free-breathing 3D Stack-of-Stars Gradient Echo Sequence in MR-guided Percutaneous Liver Interventions: Evaluation of Workflow and Diagnostic QualityCONCLUSION: A free-breathing 3D stack-of-stars gradient echo sequence can simplify the workflow and reduce intervention time, while providing superior image quality. Under local anesthesia, it increases patient comfort and reduces potential risks for needle dislocations in MR-guided liver interventions by avoiding respiratory arrests for needle position control.
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Free-breathing 3D Stack-of-Stars Gradient Echo Sequence in MR-guided Percutaneous Liver Interventions: Evaluation of Workflow and Diagnostic Quality
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Read more →: Free-breathing 3D Stack-of-Stars Gradient Echo Sequence in MR-guided Percutaneous Liver Interventions: Evaluation of Workflow and Diagnostic QualityCONCLUSION: A free-breathing 3D stack-of-stars gradient echo sequence can simplify the workflow and reduce intervention time, while providing superior image quality. Under local anesthesia, it increases patient comfort and reduces potential risks for needle dislocations in MR-guided liver interventions by avoiding respiratory arrests for needle position control.