Author

Michaela Segschneider

University of Bonn

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Neuroscience· 2

Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:imaging· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Arnaud OgieriD· 2 shared Johannes H. WilbertziD· 2 shared Michael PeitziD· 2 shared Oliver BrüstleiD· 2 shared Peter SommeriD· 2 shared Zahra HanifehlouiD· 2 shared Amélie Weiss· 1 shared Aurore VuideliD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

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2 shared papersNeuroscience

Arnaud OgierORCID

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2 papers

Recent·Most cited

Mapping human microglial morphological diversity via handcrafted and deep learning-derived image features

Kayhan Alvandipour, Amélie Weiss, Mona Mathews, Brenda Besemer, Michaela Segschneider, Zahra Hanifehlou, Christian Felski, Michael Peitz, Arnaud Ogier, Peter Sommer, Oliver Brüstle, Johannes H. Wilbertz

The paper develops an imaging and analysis framework to map human microglial activation states using handcrafted and deep learning features, showing deep learning features achieve high classification accuracy and correlate with biological states.

iScience · Jun 27, 2026Peer-reviewedNeuroscience

Machine learning-aided multidimensional phenotyping of Parkinson's disease patient stem cell-derived midbrain dopaminergic neurons

Aurore Vuidel, Loïc Cousin, Beatrice Weykopf, Simone Haupt, Zahra Hanifehlou, Nicolas Wiest-Daesslé, Michaela Segschneider, Michael Peitz, Arnaud Ogier, Laurent Brino, Oliver Brüstle, Peter Sommer, Johannes H. Wilbertz

The paper uses machine learning to classify Parkinson's disease patient-derived midbrain dopaminergic neurons based on multiple image-based phenotypes and identifies treatable targets.

bioRxiv · Mar 1, 2022 · PreprintNeuroscience