ArticleThe European journal of neuroscience2018
Implementation of deep neural networks to count dopamine neurons in substantia nigra.
Article in The European journal of neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Construct optimization for AAV-mediated human α-syn overexpression, and validation across research settings: Development of a shared tool for the research community.Journal of Parkinson's disease · 2026Article
- Effects of chemogenetic inhibition of serotonergic raphe-striatal neurons on L-DOPA-induced behaviors and neurochemistry in a rat model of Parkinson's disease.Acta neuropathologica communications · 2026Article
- MiniPromoters Ple384 (TH) and Ple388 (PITX3) for targeting midbrain dopaminergic neurons in mice and monkeys.Scientific reports · 2026Article
- Introducing PIGMO, a novel PIGmented MOuse model of Parkinson's disease.NPJ Parkinson's disease · 2026Article
- Evaluation of a commercial AI-assisted cell counting software for dopaminergic neurons across species.PloS one · 2026Article
- Development of convolutional neural networks for automated brain-wide histopathological analysis in mouse models of synucleinopathies.NPJ Parkinson's disease · 2025Article
- An injury-associated lobular microniche is associated with the classical tumor cell phenotype in pancreatic cancer.Nature communications · 2025Article
- Improving early detection of Alzheimer's disease through MRI slice selection and deep learning techniques.Scientific reports · 2025Article
- Alterations in functional and structural connectivity in the 6-OHDA-induced Parkinsonian rat model.Frontiers in neuroscience · 2025Article
- Engineered AAV capsid transport mutants overcome transduction deficiencies in the aged CNS.Molecular therapy. Nucleic acids · 2024Article
- Dynamic changes in AI-based analysis of endometrial cellular composition: Analysis of PCOS and RIF endometrium.Journal of pathology informatics · 2024Article
- AI-algorithm training and validation for identification of endometrial CD138+ cells in infertility-associated conditions; polycystic ovary syndrome (PCOS) and recurrent implantation failure (RIF).Journal of pathology informatics · 2024Article
- Deep learning assisted quantitative analysis of Aβ and microglia in patients with idiopathic normal pressure hydrocephalus in relation to cognitive outcome.Journal of neuropathology and experimental neurology · 2024Article
- Investigation in the cannabigerol derivative VCE-003.2 as a disease-modifying agent in a mouse model of experimental synucleinopathy.Behavioral and brain functions : BBF · 2024Article
- Heterozygous loss of Engrailed-1 and α-synucleinopathy (En1/SYN): A dual-hit preclinical mouse model of Parkinson's disease, analyzed with artificial intelligence.Neurobiology of disease · 2024Article
- Delivery of CDNF by AAV-mediated gene transfer protects dopamine neurons and regulates ER stress and inflammation in an acute MPTP mouse model of Parkinson's disease.Scientific reports · 2024Article
- Manually pressurized droplet digital PCR chip for rapid SARS-CoV-2 diagnostics.Biomicrofluidics · 2024Article
- The effects of chemogenetic targeting of serotonin-projecting pathways on L-DOPA-induced dyskinesia and psychosis in a bilateral rat model of Parkinson's disease.Frontiers in neural circuits · 2024Article
- Development and characterization of a non-human primate model of disseminated synucleinopathy.Frontiers in neuroanatomy · 2024Article
- Deep learning-based image analysis identifies a DAT-negative subpopulation of dopaminergic neurons in the lateral Substantia nigra.Communications biology · 2023Article
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9 authors.
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Abstract
Unbiased estimates of neuron numbers within substantia nigra are crucial for experimental Parkinson's disease models and gene-function studies. Unbiased stereological counting techniques with optical fractionation are successfully implemented, but are extremely laborious and time-consuming. The development of neural networks and deep learning has opened a new way to teach computers to count neurons. Implementation of a programming paradigm enables a computer to learn from the data and development of an automated cell counting method. The advantages of computerized counting are reproducibility, elimination of human error and fast high-capacity analysis. We implemented whole-slide digital imaging and deep convolutional neural networks (CNN) to count substantia nigra dopamine neurons. We compared the results of the developed method against independent manual counting by human observers and validated the CNN algorithm against previously published data in rats and mice, where tyrosine hydroxylase (TH)-immunoreactive neurons were counted using unbiased stereology. The developed CNN algorithm and fully cloud-embedded Aiforia™ platform provide robust and fast analysis of dopamine neurons in rat and mouse substantia nigra.
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