Add -- Winter School 2021 Day 2: add speakers names and session titles, as well as intro slides

HIBALL WS21 – The BigBrain Warp

A tutorial about Integrating BigBrain with MRI using The BigBrain Warp HIBALL Winter School 2021 – BigBrain data and tools, Feb 4, 2021

Casey Paquola, Institute of Neuroscience and Medicine, Structural and functional organisation of the brain (INM-1), Forschungszentrum Jülich, Germany Boris Bernhardt, McGill Centre for Integrative Neuroscience, McGill University, Canada

The BigBrain Warp is a toolbox for multi-modal integration of BigBrain, composed of a centralised repository of BigBrain related transformations and scripts to easily move between histological and MRI spaces. This session introduces the toolbox and presents short tutorials on how to use BigBrain in the context of structural and functional MRI.

links: The BigBrain Warp: https://bigbrainwarp.readthedocs.io/en/latest/

BigBrainProject https://bigbrainproject.org/ HIBALL https://bigbrainproject.org/hiball.html

INM-1 https://www.fz-juelich.de/inm/inm-1/EN/Home/home_node.html FZJ https://www.fz-juelich.de/portal/EN/Home/home_node.html

HIBALL WS21 – VoluBA

A tutorial on how to anchoring partial volumetric data to BigBrain using VoluBA HIBALL Winter School 2021 – BigBrain data and tools, Feb 4, 2021

Timo Dickscheid, Sebastian Bludau, Institute of Neuroscience and Medicine, Structural and functional organisation of the brain (INM-1), Forschungszentrum Jülich, Germany

VoluBA ("Volumetric Brain Anchoring") is an online service which allows to upload a high-resolution volume of interest (VOI) to perform interactive anchoring to the BigBrain, without the need of downloading the BigBrain volume to a local machine. VoluBA provides fast and intuitive manipulation of the 3D position, orientation, and scale of the VOI. Furthermore, it allows to precisely enter pairs of corresponding 3D landmarks and use them to refine the alignment by 3D affine parameters. In addition, a plugin is available for subsequent nonlinear adjustment of cortical VOIs, which exploits equivolumetric volumetric depth as a constraint in case that a segmentation of the gray matter is available. This tutorial provides a hands-on introduction to VoluBA, using a real world example dataset.

links: VoluBA: https://voluba.apps.hbp.eu/#/

BigBrainProject https://bigbrainproject.org/ HIBALL https://bigbrainproject.org/hiball.html

INM-1 https://www.fz-juelich.de/inm/inm-1/EN/Home/home_node.html FZJ https://www.fz-juelich.de/portal/EN/Home/home_node.html

HIBALL WS21 – Algorithms for Segmenting the Brain

A tutorial on algorithms for segmenting the Brain, from thresholding to deep neural networks HIBALL Winter School 2021 – BigBrain data and tools, Feb 4, 2021

Thomas Funck, Institute of Neuroscience and Medicine, Structural and functional organisation of the brain (INM-1), Forschungszentrum Jülich, Germany

This tutorial gives a brief overview and hands on examples for common techniques that can be used to segment brain images. It starts by looking at simple, but powerful, histogram thresholding, before touching on some common machine learning techniques, ending with a look at neural networks. This session is not a deep dive into any of these topics but instead aims to give participants an idea of what tools are available, how to use them, and their limitations. Ideally, participants should have a basic understanding of python, but this is not strictly necessary.

links: example notebook: https://github.com/tfunck/hiball_winter_school_2021

BigBrainProject https://bigbrainproject.org/ HIBALL https://bigbrainproject.org/hiball.html

INM-1 https://www.fz-juelich.de/inm/inm-1/EN/Home/home_node.html FZJ https://www.fz-juelich.de/portal/EN/Home/home_node.html

HIBALL WS21 – the BigBrain atlas of cortical layers

At tutorial on working with the BigBrain atlas of cortical layers HIBALL Winter School 2021 – BigBrain data and tools, Feb 4, 2021

Konrad Wagstyl, Wellcome Centre for Human Neuroimaging, University College London, UK

This tutorial provides examples for how to interact with the laminar atlas of the BigBrain using jupyter notebooks and python. Different exmaples are presented using the segmented BigBrain volume, mesh surfaces and surface-based maps of laminar thickness and intensity, as well as basic tools for visualising the data.

links: data and example notebooks: https://github.com/kwagstyl/cortical_layers_tutorial cortical layers at the EBRAINS Multilevel Human Atlas: https://atlases.ebrains.eu/viewer/?templateSelected=Big+Brain+%28Histology%29&parcellationSelected=Cortical+Layers+Segmentation&cNavigation=0.0.0.-W000..2_ZG29.-ASCS.2-8jM2._aAY3..BSR0..6OMi.iVpO%7E.JPgu%7E..1jtG

BigBrainProject https://bigbrainproject.org/ HIBALL https://bigbrainproject.org/hiball.html

Wellcome Centre for Human Neuroimaging: https://www.fil.ion.ucl.ac.uk/ UCL: http://ucl.ac.uk/

HIBALL WS21 – MicroDraw

An interactive tutorial on collaborative segmentation and analysis of histological data on the Web using MicroDraw HIBALL Winter School 2021 – BigBrain data and tools, Feb 4, 2021

Katja Heuer, CRI Centre de Recherche Interdisciplinaire Roberto Toro, Department of Neuroscience, Institut Pasteur Nicolas Traut, CRI Centre de Recherche Interdisciplinaire

High resolution histological data provides a unique perspective on the cellular structure of the brain. Histological data is available for a large number of species, and the possibility of staining for particular aspects of the tissue allows the researcher to formulate an extremely rich range of questions. It presents, however, several challenges which make its analysis difficult. In particular, the data is affected by various types of artefact, and the subtle differences that distinguish one structure from the other require a well trained human eye. In addition, scanned at very high resolution, the file sizes involved become difficult to manipulate. These may be in part the reasons why the expert segmentation of histological material is often performed by a single researcher. MicroDraw is an online tool for the collaborative segmentation of high-resolution histological data. MicroDraw uses deepzoom to enable rapid access to high-resolution data without limits in image size. Images can be manipulated in any Web browser, in computers, tablets or even smart phones. MicroDraw provides a growing number of tools for vectorial annotation, which allow us to segment data at any resolution. MicroDraw greatly simplifies distributed collaboration, by providing researchers access to the same dataset independently of the computer where the data is hosted. MicroDraw provides simple tools for the definition of collaborative projects, and helps coordinate access to data and results. Finally, MicroDraw implements a RESTful API, which allows researchers to programmatically query the segmentations performed in a project and use sophisticated image analysis tools for their analysis. This tutorial shows how to encode data and host it to make it accessible, how to visualise data and annotate it using the different vectorial annotation tools, how to create a project to centralise a set of annotations. Finally it shows how to query that data using a Python script, display the data obtained and compute some simple measurements. MicroDraw is open source and we invite you to contribute to its development either as a user or as a developer.

links: notebook: https://colab.research.google.com/github/neuroanatomy/microdraw-tutorials/blob/main/MicroDraw_SquirrelMonkey.ipynb MicroDraw: https://microdraw.pasteur.fr/

BigBrainProject https://bigbrainproject.org/ HIBALL https://bigbrainproject.org/hiball.html

Neuroscience, Institut Pasteur: https://www.pasteur.fr/en/our-missions/research/neuroscience CRI: https://www.cri-paris.org/en

3design / 3design.github.io

Add -- Winter School 2021 Day 2: add speakers names and session titles, as well as intro slides #93