1 Max Planck Research Group for Neuroanatomy & Connectivity, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1a, Leipzig, 04103, Germany.
2 Neurocomputation and Neuroimaging Unit, Department of Education and Psychology, Free University of Berlin, Habelschwerdter Allee 45, Berlin, 14195, Germany.
3 Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1a, Leipzig, 04103, Germany.
4 Cerebral Imaging Center, Douglas Mental Health University Institute, 6875 LaSalle Boulevard, Montreal, Quebec, H4H 1R3, Canada.
5 Department of Psychology, Concordia University, 7141 Sherbrooke West, Montreal, Quebec, H4B IR6, Canada.
6 Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1a, Leipzig, 04103, Germany.
7 Psychology Department, University of Amsterdam, Nieuwe Achtergracht 129B, Amsterdam, 1018 WT, Netherlands.

With recent improvements in human magnetic resonance imaging (MRI) at ultra-high fields, the amount of data collected per subject in a given MRI experiment has increased considerably. Standard image processing packages are often challenged by the size of these data. Dedicated methods are needed to leverage their extraordinary spatial resolution. Here, we introduce a flexible Python toolbox that implements a set of advanced techniques for high-resolution neuroimaging. With these tools, segmentation and laminar analysis of cortical MRI data can be performed at resolutions up to 500 µm in reasonable times. Comprehensive online documentation makes the toolbox easy to use and install. An extensive developer's guide encourages contributions from other researchers that will help to accelerate progress in the promising field of high-resolution neuroimaging.