ArticleNature methods2020
Machine learning analysis of whole mouse brain vasculature.
Article in Nature methods, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 174 papers.
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Who cites it
174 citing papers in PubMed, 337 citations in OpenAlex.
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- Chinese expert concern and consensus on applications of artificial intelligence in clinical cancer imaging.Insights into imaging · 2026Article
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- VesSynth: Tubes Are All You Need for Robust Cross-Scale Cross-Modal 3D Vessel Segmentation.bioRxiv : the preprint server for biology · 2026Article
- User-preference alignment with uncertainty-aware interactive rectification for liver organ and tumor segmentation and analysis from CT images.NPJ digital medicine · 2026Article
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- mViSE: A visual search engine for analyzing multiplex IHC brain tissue images (spatial proteomics).Scientific reports · 2026Article
- The stroke risk gene Foxf2 maintains brain endothelial cell function via Tie2 signaling.Nature neuroscience · 2026Article
- A spatiotemporal atlas of cerebrovascular development in zebrafish.Nature communications · 2026Article
- Involvement of Secondary Induced Thrombus on Hemorrhage Induced by Both Delayed Recanalization and Delayed t-PA Treatment in Murine Ischemic Stroke Models.Biomedicines · 2026Article
- Microvascular architecture and physiological fluctuations constrain the control of cerebral microcirculation.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Anatomically aware simulation of patient-specific glioblastoma xenografts.PLoS computational biology · 2026Article
- A high-resolution dataset of mouse brain vasculature for deep learning-based reconstruction.Frontiers in neuroinformatics · 2026Article
- Rapid 3D Immunolabeling and Light Sheet Microscopy for Quantitative Analysis of Intact Tissues.Computational and structural biotechnology journal · 2026Article
- 3D vascular mapping reveals multi-organ injury following severe acute pancreatitis.Theranostics · 2026Article
114 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
12 authors at 7 institutions in 3 countries.
Funding
Abstract
Tissue clearing methods enable the imaging of biological specimens without sectioning. However, reliable and scalable analysis of large imaging datasets in three dimensions remains a challenge. Here we developed a deep learning-based framework to quantify and analyze brain vasculature, named Vessel Segmentation & Analysis Pipeline (VesSAP). Our pipeline uses a convolutional neural network (CNN) with a transfer learning approach for segmentation and achieves human-level accuracy. By using VesSAP, we analyzed the vascular features of whole C57BL/6J, CD1 and BALB/c mouse brains at the micrometer scale after registering them to the Allen mouse brain atlas. We report evidence of secondary intracranial collateral vascularization in CD1 mice and find reduced vascularization of the brainstem in comparison to the cerebrum. Thus, VesSAP enables unbiased and scalable quantifications of the angioarchitecture of cleared mouse brains and yields biological insights into the vascular function of the brain.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.