Comment on "Developing DCE-CT to Quantify Intra-Tumor Heterogeneity in Breast Tumors With Differing Angiogenic Phenotype". - Andrij Abramyuk; Gunter Wolf; Volker Hietschold; Ulrike Haberland; Joerg van den Hoff; Nasreddin Abolmaali (IEEE Trans. Medical Imaging, 2010)

Swarm Intelligence for Medical Volume Segmentation: The Contribution of Self-reproduction. - Robert Haase 001; Hans-Joachim Böhme; Daniel Zips; Nasreddin Abolmaali (KI, 2011)

Self-reproduction versus Transition Rules in Ant Colonies for Medical Volume Segmentation. - Robert Haase 001; Hans-Joachim Böhme; Rosalind Perrin; Klaus Zöphel; Nasreddin Abolmaali (ANTS, 2012)

Landmark-based evaluation of a deformable motion correction for DCE-MRI of the liver. - Jan Strehlow; Nadine Spahr; Jan Rühaak; Hendrik Laue; Nasreddin Abolmaali; Tobias Preusser; Andrea Schenk (Int. J. Comput. Assist. Radiol. Surg., 2018)

Multimodal image registration for liver radioembolization planning and patient assessment. - Nadine Spahr; Smita Thoduka; Nasreddin Abolmaali; Ron Kikinis; Andrea Schenk (Int. J. Comput. Assist. Radiol. Surg., 2019)

Improving deep learning based liver vessel segmentation using automated connectivity analysis. - Felix Thielke; Farina Kock; Annika Hänsch; Joachim Georgii; Nasreddin Abolmaali; Itaru Endo; Hans Meine; Andrea Schenk (Image Processing, 2022)

Abstract: Liver Tumor Segmentation in Late-phase MRI using Multi-model Training and an Anisotropic U-Net. - Annika Gerken; Grzegorz Chlebus; Hans Meine; Felix Thielke; Farina Kock; Tobias Paulus; Nasreddin Abolmaali; Andrea Schenk (Bildverarbeitung für die Medizin, 2023)

Combining arterial and venous CT scans in a multi-encoder network for improved hepatic vessel segmentation. - Felix Thielke; Farina Kock; Annika Hänsch; Nasreddin Abolmaali; Andrea Schenk; Hans Meine (Image Processing, 2023)

Suitability of DNN-based vessel segmentation for SIRT planning. - Farina Kock; Felix Thielke; Nasreddin Abolmaali; Hans Meine; Andrea Schenk (Int. J. Comput. Assist. Radiol. Surg., 2024)