# Welcome to the web page for the 1st Get Your Brain Straight Hackathon ! ## What? The **Get Your Brain Straight** hackathons **bring together neuroimage data generators, image registration researchers, and neurodata compute infrastructure providers for a hands-on, collaborative event**. This community collaboration aims to **create reproducible, open source resources** that enable discovery of the structure and function of brains. There are three components to the hackathon. First, the primary goal of each hackathon is the generation of a **Reproducible Resource** for registration and analysis of a specific brain imaging modality. **Tutorial** sessions share how to work with open source registration tools, open access datasets, or neurodata archives. **Birds-of-a-Feather (BOF) Breakout** sessions enable participants interested in collaborating to work on relevant topics. **Example ways to participate:** * [Contribute a registration pipeline resource](https://insightsoftwareconsortium.github.io/GetYourBrainStraight/HCK01_2022_Virtual/#reproducible-resource-challenge) that can be deployed on Brain Imaging Library (BIL) resources to register the challenge dataset. * [Give a tutorial](https://insightsoftwareconsortium.github.io/GetYourBrainStraight/HCK01_2022_Virtual/#tutorials) about your registration tools. A pre-recorded or live presentation, along with example code and recipes, can teach a data analyst how to run your tool and use the output on the challenge dataset and/or another open dataset. * [Come and learn](https://insightsoftwareconsortium.github.io/GetYourBrainStraight/HCK01_2022_Virtual/#birds-of-a-feather-breakouts) about registration from experts in the field. ## When, where, how much? - **Dates:** Monday, April 4th - Thursday, April 7th, 2022 - **Location:** The first hackathon will be online, held on [Zoom](https://alleninstitute-org.zoom.us/j/96111568520?pwd=c2U2UXlFWmdHWVhjWWNUL3V2OWJQZz09) videoconferencing, [Image.sc Island Gather.Town](https://j.mp/imagesc-island) virtual space, and [Image.sc Zulip Chat](https://imagesc.zulipchat.com/). - **Registration:** Fees: none, it's free! Use [this form](https://forms.gle/eJEf7yQq4UeSc1zF9) to register. Deadline: April 2nd. - **Communication:** to receive information about this and future events please join the [Hackathon Mailing List](https://groups.google.com/g/brain_straight_hackathon_announcements). ## How does it work? ### Before the Hackathon - [Register](https://forms.gle/eJEf7yQq4UeSc1zF9) for the event. There is no cost. - Sign up for the [mailing list](https://groups.google.com/g/brain_straight_hackathon_announcements). - [Set up an account](https://www.brainimagelibrary.org/computevisual.html) at the Brain Image Library (BIL). - Optionally prepare a tutorial or organize a Birds-of-a-Feather (BoF) Breakout, described below. ### During the Hackathon The week will start 8 AM Pacific Time, 11 AM Eastern Time, Monday, April 4th in an introductory all-hands videoconference. Following the introduction, participate in the [Reproducible Resource Challenge](#reproducible-resource-challenge), join the [tutorials](#tutorials), and participate [BoF breakouts](#birds-of-a-feather-breakouts). On Thursday, 11 AM Pacific Time, 2 PM Eastern Time, participants will delegate one member to present their registration processing pipelines, results, and discuss lessons learned. ## Who can attend? Get Your Brain Straight hackathons are open to all and publicly advertised. Email announcements are sent to the [mailing list](https://groups.google.com/g/brain_straight_hackathon_announcements). ## Agenda

[How to add this calendar to your own?](../common/Calendar.md) ## Reproducible Resource Challenge This aim of this hackathon is to generate reproducible pipelines to register whole-brain microscopy image data to the [CCFv3](https://doi.org/10.1016/j.cell.2020.04.007). Two datasets are provided, each with their unique quirks. You may work on either dataset during the hackathon. In order to work with the neuroimage data generators, these pipelines will take a standardized input without assumptions of directory structures, filenames, etc and generate standardized outputs. Expected outputs include: resampled brain, spatial transformation, and a manifest of outputs. The processing pipelines should be designed to executed in independently in parallel. The output should be a resampled image with the same size, orientation, and origin as the provided CCFv3. The output should include an affine transformation file, and a deformation field transformation file to transform SWC and/or annotation files from the challenge dataset image space into the CCFv3 space. Criteria for inclusion in a summary paper: - [ ] Open source with an [OSI-approved license](https://opensource.org/licenses) - The code can be executed in the future - Researchers can understand what the code is doing - Researchers can extend or fix as needed - Works on open standard data formats used by data providers and consumers - [ ] NIFTI images - Deployable - Can be executed across many environments - [ ] Provided in a published [singularity](https://sylabs.io/guides/2.6/user-guide/introduction.html) image - [ ] Can be executed by an independent analyst on the BIL The primary goals for this hackathon is to ensure that everyone's code can run on the dataset provided and can be replicated. In future hackathons, we will focus on: - Combine registration results and methods - Quantification and characterization of deformation patterns in fMOST imaging - Identify biologically relevant regions where improvements need to be made - Focus on accuracy quantification leading to potential improvements [How to add a new reproducible registration processing pipeline?](./ReproducibleResource/README.md) ### Challenge Dataset 1: fMOST Mouse Brain Registration to CCFv3 The fMOST brain volumes and CCFv3 atlas for the hackathon are available [on the BIL here](https://download.brainlib.org/hackathon/2022_GYBS/input/fMOST/). The input is a single fMOST NIFTI brain volume. Details about this dataset can be found [here](./Tutorials/fMOSTIntroduction). ### Challenge Dataset 2: Light-Sheet Imaged Mouse Brain Registration to CCFv3 The Light-sheet imaged brain volumes are available [on the BIL here](https://download.brainlib.org/hackathon/2022_GYBS/input/lightsheet/). For this challenge set, the data and atlas is provided for a single brain hemisphere (for size considerations and to mimic most real world experiments). Multiple data replicates are provided. We provide one dataset `subject0.zarr` in full imaging resolution for those seeking a bigger challenge. As a convenience we provide the challenge sets at approximately atlas size as Nifti(`subjectN_25.nii.gz`) or [OME-NGFF](`subjectN_25.nii.gz`) (`subjectN_25.zarr`). Participants may use either format but OME-NGFF is preferred because it allows more efficient memory usage for larger datasets. Details on working with the data can be found [here](./Tutorials/MappingLightSheetData/AboutTheDatasets.md) ## Tutorials Tutorial sessions share how to work with open source registration tools, open access datasets, or neurodata ### Monday 4/4 - Brain Imaging Library (BIL), 1 PM-3 PM ET, (Ivan Cao-Berg, Greg Hood, Alex Ropelewski) - [Get Your Brain Pipelined](./Tutorials/GetYourBrainPipelined), 3 PM ET, (Jeff Duda, Min Chen, Jim Gee) - [About the Challenge Dataset](./Tutorials/fMOSTIntroduction), 3:30 PM ET, (Lydia Ng) - [Registering Cleared Tissues](./Tutorials/MappingLightSheetData/MappingLightSheet.md), 4 PM ET, (Ricardo Azevedo) ### Tuesday 4/5 - [ITKElastix Image Registration Tutorial](./Tutorials/ITKElastixTutorial.md), 10:30-11 AM ET (Viktor van der Valk, Matt McCormick) - [Metadata Preservation for Image Registration](./Tutorials/MetadataPreservation/MetadataPreservation.md), 1-2 PM ET, (Matt McCormick, Lydia Ng, Dženan Zukić) - [Image Registration with a Maximization Minorization (MM) Optimization Algorithm](./Tutorials/MMOptimizationAlgorithm.md), 12:30-1 PM ET (Daniel Tward, Gary Zhou, Ken Langea) - [Your Transform Object Needs Metadata](./Tutorials/YourTransformObjectNeedsMetadata.md), 4-4:45 PM ET (Hastings Greer) ### Wednesday 4/6 - [OME-NGFF: Towards a community standard image file format for sharing big image data in the cloud](https://globalbioimaging.org/international-training-courses/ome-ngff-workshop-2022), 8-11 AM ET, (Christian Tischer, Josh Moore) - *Sister event -- requires additional registration* - [Mapping Micro to Macro Scale Anatomy with LDDMM](./Tutorials/MappingMicroToMacroScaleAnatomyWithLDDMM.md), 12-1 PM ET, (Kaitlin Stouffer, Bryson Gray, Michael Miller, Daniel Tward) [How to add a new tutorial?](./Tutorials/README.md) ## Birds-of-a-Feather Breakouts Birds-of-a-Feather (BOF) breakout sessions enable participants interested in collaborating to work on relevant topics. To lead or join a Birds-of-a-Feather (BoF) breakout session, create or join a topic [in this spreadsheet](https://docs.google.com/spreadsheets/d/1uthoU0CbY-sN5e4neY70IsHKPPXkR21fkcamMDJtmrg/edit#gid=0). During the BoF, find the leader by clicking on their name in the [Image.sc Island Gather.Town](https://j.mp/imagesc-island) and moving towards their avatar with the keyboard arrow keys. When you are close to their avatar in the virtual space, you will be able to see, hear, and talk to each other. If notes are taken during the BoF, please add them to the [BoF breakouts folder](./BoFBreakouts). We recommend [HackMD](https://hackmd.io/) for collaborative, well-formatted notetaking. ## Code of Conduct Participants and contributors are expected to adhere to the [ITK Code of Conduct](https://github.com/InsightSoftwareConsortium/ITK/blob/master/CODE_OF_CONDUCT.md). ## Participants Registered participants: 1. Yufei Chen, AHU 2. oylei, AHU 3. Alice, Allen Institute for Brain Science 4. Pamela Baker, Allen Institute for Brain Science 5. Lydia Ng, Allen Institute for Brain Science 6. Rachel Dalley, Allen Institute for Brain Science 7. Li, Anhui University 8. Yuxiao Zhang, Anhui University 9. tingtinghan, Anhui University 10. Tingting Han, Anhui University 11. Jesse, Anhui University 12. Liyunayuan, Anhui University 13. Iana Vasylieva, Center for Biologic Imaging, University of Pittsburgh 14. Adrian Arias Abreu, Centre for Genomic Regulation 15. Stuart gano, Google 16. John Bogovic, HHMI Janelia 17. Bin Duan, Illinois Tech 18. Can Ceritoglu, JHU Center for Imaging Science 19. Kaitlin Stouffer, Johns Hopkins University 20. Thomas Athey, Johns Hopkins University 21. Brock Wester, Johns Hopkins University Applied Physics Laboratory 22. Erik Johnson, Johns Hopkins University Applied Physics Laboratory 23. Dzenan Zukic, Kitware 24. Tom Birdsong, Kitware 25. Will Schroeder, Kitware 26. Matt McCormick, Kitware 27. Paul Elliott, Kitware 28. Ebrahim Ebrahim, Kitware 29. Viktor van der Valk, LKEB - LUMC 30. Brian Eastwood, MBF Bioscience 31. Kara, N/A 32. Fae Kronman, Penn State University 33. Yongsoo Kim, Penn State University 34. Art Wetzel, Pittsburgh Supercomputing Center 35. Mariah Kenney, Pittsburgh Supercomputing Center 36. Luke Tuite, Pittsburgh Supercomputing Center 37. Greg Hood, Pittsburgh Supercomputing Center / CMU 38. Alexander Ropelewski, PSC 39. Xin Wu, RTI International 40. Zhixi Yun, SEU 41. Adam Aji, SonoVol 42. Yufeng Liu, Southeast University 43. Tony Reksoatmodjo, Translucence Biosystems 44. Kate Lawson, UC Irvine 45. Ricardo Azevedo, UC Irvine 46. Negin, UC Irvine 47. Jaclyn Beck, UC Irvine 48. Zhongkai Wu, UC San Diego 49. Christopher Choi, UCLA 50. Daniel Tward, UCLA 51. Ian Bowman, UCLA BRAIN 52. Luis, UCLA BRAIN 53. Karl Marrett, UCLA Computer Science, VAST lab 54. Guorong Wu, UNC Chapel Hill 55. Hyejin Yang, UNC Chapel Hill 56. Sarah Khan, UNC Chapel Hill 57. Marc Niethammer, UNC Chapel Hill 58. Carolyn McCormick, UNC Chapel Hill 59. Min Chen, University of Pennsylvania 60. Jeffrey Duda, University of Pennsylvania 61. Alan Watson, University of Pittsburgh 62. Nick Tustison, University of Virginia 63. brian, University of Virginia ## Acknowledgements This hackathon is supported by the National Institute of Mental Health (NIMH) of the National Institutes of Health (NIH) under the [BRAIN Initiative](https://braininitiative.nih.gov/) award numbers [1RF1MH126732](https://projectreporter.nih.gov/project_info_description.cfm?aid=10259930), [1U19MH114830-01](https://projectreporter.nih.gov/project_info_description.cfm?aid=9416007), [5R24MH114793-02](https://reporter.nih.gov/project-details/9567623), [1U24MH114827-01](https://reporter.nih.gov/project-details/9415946) and the [BICCN](https://biccn.org/).