Supervised segmentation methods for the hippocampus in MR images. - Marijn van Stralen; Mirjam I. Geerlings; Koen L. Vincken; Josien P. W. Pluim (Image Processing, 2011)

Microbleeds, lacunar infarcts, white matter lesions and cerebrovascular reactivity - A 7 T study. - Mandy M. A. Conijn; Johannes M. Hoogduin; Yolanda van der Graaf; Jeroen Hendrikse; Peter R. Luijten; Mirjam I. Geerlings (NeuroImage, 2012)

Efficient detection of cerebral microbleeds on 7.0 T MR images using the radial symmetry transform. - Hugo J. Kuijf; Jeroen de Bresser; Mirjam I. Geerlings; Mandy M. A. Conijn; Max A. Viergever; Geert Jan Biessels; Koen L. Vincken (NeuroImage, 2012)

Subfields of the hippocampal formation at 7 T MRI: In vivo volumetric assessment. - Laura E. M. Wisse; L. Gerritsen; Jaco J. M. Zwanenburg; Hugo J. Kuijf; Peter R. Luijten; Geert Jan Biessels; Mirjam I. Geerlings (NeuroImage, 2012)

Automatic Extraction of the Midsagittal Surface from Brain MR Images using the Kullback-Leibler Measure. - Hugo J. Kuijf; Susanne J. van Veluw; Mirjam I. Geerlings; Max A. Viergever; Geert Jan Biessels; Koen L. Vincken (Neuroinformatics, 2014)

Quantitative comparison of 21 protocols for labeling hippocampal subfields and parahippocampal subregions in in vivo MRI: Towards a harmonized segmentation protocol. - Paul A. Yushkevich; Robert S. C. Amaral; Jean C. Augustinack; Andrew R. Bender; Jeffrey D. Bernstein; Marina Boccardi; Martina Bocchetta; Alison C. Burggren; Valerie A. Carr; M. Mallar Chakravarty; Gaël Chételat; Ana M. Daugherty; et al. (NeuroImage, 2015)

Erratum to "Subfields of the hippocampal formation at 7T MRI: In vivo volumetric assessment" [NeuroImage 61 (2012) 1043-1049]. - Laura E. M. Wisse; L. Gerritsen; Jaco J. M. Zwanenburg; Hugo J. Kuijf; Peter R. Luijten; Geert Jan Biessels; Mirjam I. Geerlings (NeuroImage, 2016)

MixLacune: Segmentation of lacunes of presumed vascular origin. - Denis Kutnar; Bas H. M. van der Velden; Marta Gironés-Sangüesa; Mirjam I. Geerlings; J. Matthijs Biesbroek; Hugo J. Kuijf (CoRR, 2021)

Dementia prediction in the general population using clinically accessible variables: a proof-of-concept study using machine learning. The AGES-Reykjavik study. - Emma L. Twait; Constanza L. Andaur Navarro; Vilmundur Gudnason; Yi-Han Hu; Lenore J. Launer; Mirjam I. Geerlings (BMC Medical Informatics Decis. Mak., 2023)