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The ANTsX ecosystem for mapping the mouse brain.

November 22, 2025pubmed logopapers

Authors

Tustison NJ,Chen M,Kronman FN,Duda JT,Gamlin C,Tustison MG,Kunst M,Dalley R,Sorenson S,Wang Q,Ng L,Kim Y,Gee JC

Affiliations (6)

  • Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA. [email protected].
  • Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
  • Department of Neuroscience and Experimental Therapeutics, Penn State University, Hershey, PA, USA.
  • Allen Institute for Brain Science, Seattle, WA, USA.
  • Santiago High School, Corona, CA, USA.
  • Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA. [email protected].

Abstract

Large-scale efforts by the BRAIN Initiative Cell Census Network (BICCN) are generating a comprehensive reference atlas of cell types in the mouse brain. A key challenge in this effort is mapping diverse datasets, acquired with varied imaging, tissue processing, and profiling methods, into shared coordinate frameworks. Here, we present mouse brain mapping pipelines developed using the Advanced Normalization Tools Ecosystem (ANTsX) to align MERFISH spatial transcriptomics and high-resolution fMOST morphology data to the Allen Common Coordinate Framework (CCFv3), and developmental MRI and LSFM data to the Developmental CCF (DevCCF). Simultaneously, we introduce two novel methods: 1) a velocity field-based approach for continuous interpolation across developmental timepoints, and 2) a deep learning framework for automated brain parcellation using minimally annotated and publicly available data. All workflows are open-source and reproducible. We also provide general guidance for selecting appropriate strategies across modalities, enabling researchers to adapt these tools to new data.

Topics

Journal Article

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