ArticleJournal of neuroscience methods2018
Geometry processing of conventionally produced mouse brain slice images.
Article in Journal of neuroscience methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 0 citations in OpenAlex.
- SlicesMapi: An Interactive Three-Dimensional Registration Method for Serial Histological Brain Slices.Neuroinformatics · 2025Article
- RegBoost: Enhancing mouse brain image registration using geometric priors and Laplacian interpolation.NeuroImage · 2025Article
- Molecular signatures of cortical expansion in the human foetal brain.Nature communications · 2024Article
- Automated identification of protein expression intensity and classification of protein cellular locations in mouse brain regions from immunofluorescence images.Medical & biological engineering & computing · 2024Article
- Molecular signatures of cortical expansion in the human fetal brain.bioRxiv : the preprint server for biology · 2024Article
- Article
- Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images.bioRxiv : the preprint server for biology · 2023Article
- BoutonNet: an automatic method to detect anterogradely labeled presynaptic boutons in brain tissue sections.Brain structure & function · 2022Article
- Expected affine: A registration method for damaged section in serial sections electron microscopy.Frontiers in neuroinformatics · 2022Article
- ARMBIS: accurate and robust matching of brain image sequences from multiple modal imaging techniques.Bioinformatics (Oxford, England) · 2019Article
- Exploiting Gene Expression Profiles for the Automated Prediction of Connectivity between Brain Regions.International journal of molecular sciences · 2019Article
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3 authors at 1 institution in 1 country.
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Abstract
backgroundBrain mapping research in most neuroanatomical laboratories relies on conventional processing techniques, which often introduce histological artifacts such as tissue tears and tissue loss. NEW
methodIn this paper, we present techniques and algorithms for automatic registration and 3D reconstruction of conventionally produced mouse brain slices in a standardized atlas space. This is achieved first by constructing a virtual 3D mouse brain model from annotated slices of Allen Reference Atlas (ARA). Virtual re-slicing of the reconstructed model generates ARA-based slice images corresponding to the microscopic images of histological brain sections. These image pairs are aligned using a geometric approach through contour images. Histological artifacts in the microscopic images are detected and removed using Constrained Delaunay Triangulation before performing global alignment. Finally, non-linear registration is performed by solving Laplace's equation with Dirichlet boundary conditions.
resultsOur methods provide significant improvements over previously reported registration techniques for the tested slices in 3D space, especially on slices with significant histological artifacts. Further, as one of the application we count the number of neurons in various anatomical regions using a dataset of 51 microscopic slices from a single mouse brain. COMPARISON WITH EXISTING METHOD(S): To the best of our knowledge the presented work is the first that automatically registers both clean as well as highly damaged high-resolutions histological slices of mouse brain to a 3D annotated reference atlas space.
conclusionsThis work represents a significant contribution to this subfield of neuroscience as it provides tools to neuroanatomist for analyzing and processing histological data.
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