ArticleNeuroImage2023
Tensor image registration library: Deformable registration of stand-alone histology images to whole-brain post-mortem MRI data.
Article in NeuroImage, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Microscopy-informed structural connectivity mapping in the in vivo human brain via domain adaptation.bioRxiv : the preprint server for biology · 2026Article
- An open-source stereotaxic container with an integrated cutting guide for human brain fixation during magnetic resonance imaging and sectioning for histology.bioRxiv : the preprint server for biology · 2026Article
- A pipeline to characterize spinal cord pathology in neurological disorders combining magnetic resonance microscopy and histopathology.Communications medicine · 2026Article
- Precise MRI-Histology Coregistration of Paraffin-Embedded Tissue with Blockface Imaging.bioRxiv : the preprint server for biology · 2025Article
- Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 3-Ex vivo imaging: Data processing, comparisons with microscopy, and tractography.Magnetic resonance in medicine · 2025Review
- Layer-Dependent Effect of Aβ-Pathology on Cortical Microstructure With Ex Vivo Human Brain Diffusion MRI at 7 Tesla.Human brain mapping · 2025Article
- Imaging the structural connectome with hybrid MRI-microscopy tractography.Medical image analysis · 2025Article
- SlicesMapi: An Interactive Three-Dimensional Registration Method for Serial Histological Brain Slices.Neuroinformatics · 2025Article
- Precise MRI-histology coregistration of paraffin-embedded tissue with blockface imaging.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Research on application of multiparametric MRI to predict FNCLCC grading and ki67 expression in soft tissue sarcoma biopsy pathology: Based on a CT-MRI fusion image registration method.Frontiers in oncology · 2025Article
- Linking microscopy to diffusion MRI with degenerate biophysical models: An application of the Bayesian EstimatioN of CHange (BENCH) framework.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Hippocampal connectivity patterns echo macroscale cortical evolution in the primate brain.Nature communications · 2024Article
- Three-dimensional histology reveals dissociable human hippocampal long-axis gradients of Alzheimer's pathology.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Three-dimensional histology reveals dissociable human hippocampal long axis gradients of Alzheimer's pathology.bioRxiv : the preprint server for biology · 2023Article
- An open resource combining multi-contrast MRI and microscopy in the macaque brain.Nature communications · 2023Article
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18 authors.
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Abstract
backgroundAccurate registration between microscopy and MRI data is necessary for validating imaging biomarkers against neuropathology, and to disentangle complex signal dependencies in microstructural MRI. Existing registration methods often rely on serial histological sampling or significant manual input, providing limited scope to work with a large number of stand-alone histology sections. Here we present a customisable pipeline to assist the registration of stand-alone histology sections to whole-brain MRI data.
methodsOur pipeline registers stained histology sections to whole-brain post-mortem MRI in 4 stages, with the help of two photographic intermediaries: a block face image (to undistort histology sections) and coronal brain slab photographs (to insert them into MRI space). Each registration stage is implemented as a configurable stand-alone Python script using our novel platform, Tensor Image Registration Library (TIRL), which provides flexibility for wider adaptation. We report our experience of registering 87 PLP-stained histology sections from 14 subjects and perform various experiments to assess the accuracy and robustness of each stage of the pipeline.
resultsAll 87 histology sections were successfully registered to MRI. Histology-to-block registration (Stage 1) achieved 0.2-0.4 mm accuracy, better than commonly used existing methods. Block-to-slice matching (Stage 2) showed great robustness in automatically identifying and inserting small tissue blocks into whole brain slices with 0.2 mm accuracy. Simulations demonstrated sub-voxel level accuracy (0.13 mm) of the slice-to-volume registration (Stage 3) algorithm, which was observed in over 200 actual brain slice registrations, compensating 3D slice deformations up to 6.5 mm. Stage 4 combined the previous stages and generated refined pixelwise aligned multi-modal histology-MRI stacks.
conclusionsOur open-source pipeline provides robust automation tools for registering stand-alone histology sections to MRI data with sub-voxel level precision, and the underlying framework makes it readily adaptable to a diverse range of microscopy-MRI studies.
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