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Improving deep learning based liver vessel segmentation using automated connectivity analysis.

, , , , , , , and . Medical Imaging: Image Processing, volume 12032 of SPIE Proceedings, SPIE, (2022)

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Abstract: Liver Tumor Segmentation in Late-phase MRI using Multi-model Training and an Anisotropic U-Net., , , , , , , and . Bildverarbeitung für die Medizin, page 18. Springer, (2023)Improving deep learning based liver vessel segmentation using automated connectivity analysis., , , , , , , and . Medical Imaging: Image Processing, volume 12032 of SPIE Proceedings, SPIE, (2022)Suitability of DNN-based vessel segmentation for SIRT planning., , , , and . Int. J. Comput. Assist. Radiol. Surg., 19 (2): 233-240 (February 2024)Comment on "Developing DCE-CT to Quantify Intra-Tumor Heterogeneity in Breast Tumors With Differing Angiogenic Phenotype"., , , , , and . IEEE Trans. Medical Imaging, 29 (4): 1088-1089 (2010)Combining arterial and venous CT scans in a multi-encoder network for improved hepatic vessel segmentation., , , , , and . Medical Imaging: Image Processing, volume 12464 of SPIE Proceedings, SPIE, (2023)Multimodal image registration for liver radioembolization planning and patient assessment., , , , and . Int. J. Comput. Assist. Radiol. Surg., 14 (2): 215-225 (2019)Landmark-based evaluation of a deformable motion correction for DCE-MRI of the liver., , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 13 (4): 597-606 (2018)