ArticleeLife2019
Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning.
Article in eLife, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 26 citations in OpenAlex.
- Comparing and Optimizing Tissue Clearing Protocols for Cochlear Immunostaining and 3D Reconstruction by Light-Sheet Microscopy.Journal of the Association for Research in Otolaryngology : JARO · 2026Article
- VASCilia is an open-source, deep learning-based tool for 3D analysis of cochlear hair cell stereocilia bundles.PLoS biology · 2026Article
- VASCilia (Vision Analysis StereoCilia): A Napari Plugin for Deep Learning-Based 3D Analysis of Cochlear Hair Cell Stereocilia Bundles.bioRxiv : the preprint server for biology · 2025Article
- Spiner, deep learning-based automated detection of spiral ganglion neurons in intact cochleae.iScience · 2025Article
- Potential drug targets for ovarian cancer identified through Mendelian randomization and colocalization analysis.Journal of ovarian research · 2025Article
- Mice with deficiency in Pcdh15, a gene associated with bipolar disorders, exhibit significantly elevated diurnal amplitudes of locomotion and body temperature.Translational psychiatry · 2024Article
- Large-scale annotated dataset for cochlear hair cell detection and classification.Scientific data · 2024Article
- PCP Auto Count: A Novel Fiji/ImageJ plug-in for automated quantification of planar cell polarity and cell counting.bioRxiv : the preprint server for biology · 2024Article
- PCP auto count: a novel Fiji/ImageJ plug-in for automated quantification of planar cell polarity and cell counting.Frontiers in cell and developmental biology · 2024Article
- Large-scale annotated dataset for cochlear hair cell detection and classification.bioRxiv : the preprint server for biology · 2023Article
- Three-dimensional mouse cochlea imaging based on the modified Sca/eS using confocal microscopy.Anatomical science international · 2023Article
- The hair cell analysis toolbox is a precise and fully automated pipeline for whole cochlea hair cell quantification.PLoS biology · 2023Article
- Tissue clearing technique: Recent progress and biomedical applications.Journal of anatomy · 2021Review
- Three-dimensional imaging of intact porcine cochlea using tissue clearing and custom-built light-sheet microscopy.Biomedical optics express · 2020Article
- Recent Advances in the Application of Artificial Intelligence in Otorhinolaryngology-Head and Neck Surgery.Clinical and experimental otorhinolaryngology · 2020Review
- Biomedical Applications of Tissue Clearing and Three-Dimensional Imaging in Health and Disease.iScience · 2020Review
- A Novel Technique for Imaging and Analysis of Hair Cells in the Organ of Corti Using Modified Sca/eS and Machine Learning.Bio-protocol · 2019Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
The highly organized spatial arrangement of sensory hair cells in the organ of Corti is essential for inner ear function. Here, we report a new analytical pipeline, based on optical clearing of tissue, for the construction of a single-cell resolution map of the organ of Corti. A sorbitol-based optical clearing method enabled imaging of the entire cochlea at subcellular resolution. High-fidelity detection and analysis of all hair cell positions along the entire longitudinal axis of the organ of Corti were performed automatically by machine learning-based pattern recognition. Application of this method to samples from young, adult, and noise-exposed mice extracted essential information regarding cellular pathology, including longitudinal and radial spatial characteristics of cell loss, implying that multiple mechanisms underlie clustered cell loss. Our method of cellular mapping is effective for system-level phenotyping of the organ of Corti under both physiological and pathological conditions.
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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.