Titlebook: Bildverarbeitung für die Medizin 2023; Proceedings, German Thomas M. Deserno,Heinz Handels,Thomas Tolxdorff Conference proceedings 2023 De

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Keynote: Fully Automated Bone Removal in CBCT of the Lower Body Stem,wer body stem, which includes the abdomen and pelvis, does not have a BRM for cone beam CT (CBCT). This frequently necessitates the interventionist doing a manual BRM, particularly in the pelvic area, as in the case of a prostate embolization, necessitating his exit from the interventional room.The

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Abstract: Shape-based Segmentation of Retinal Layers and Fluids in OCT Image Data,ecades. Based on its high-resolution cross-sectional images, OCT supports diagnosis of various eye diseases. For clinical examination and treatment planning, automated segmentation of individual retinal layers and pathologies is helpful. Retinal layers follow a strict topology that is not addressed

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Abstract: Liver Tumor Segmentation in Late-phase MRI using Multi-model Training and an Anisotropic on deep learning-based liver tumor segmentation have focused on contrast-enhanced CT, however dynamic contrastenhanced MRI (DCE-MRI) can yield a higher sensitivity. In this work , we demonstrate the deep learning-based segmentation of liver tumors in the late hepatocellular phase of DCE-MRI. In part

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Automatic Vertebrae Segmentation in MR Volumes,ome popular in segmenting the spine in computed tomography (CT) volumes. However, few options have been tested for magnetic resonance (MR) imaging segmentation. In this paper, we provide a comparison of three deep learning methods tackling the automatic vertebrae segmentation in MR volumes.We select

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