Author

Botond Mathe

HUN-REN Szegedi Biológiai Kutatóközpont

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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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:deep learning· 2 Assay:imaging· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Approach:experimental assay· 1

Frequent Co-Authors

Péter HorváthiD· 2 shared Réka HollandiiD· 2 shared Ábel SzkalisityiD· 1 shared Allen GoodmaniD· 1 shared András KristoniD· 1 shared Anne Elizabeth CarpenteriD· 1 shared Árpád Bálind· 1 shared Attila Kertész‐FarkasiD· 1 shared

Activity by Year

2020-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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2 shared papersBioinformatics

Péter HorváthORCID

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2 papers

Recent·Most cited

A deep learning framework for nucleus segmentation using image style transfer

Réka Hollandi, Ábel Szkalisity, Tímea Tóth, Ervin Tasnádi, Csaba Molnár, Botond Mathe, István Grexa, József Molnár, Árpád Bálind, Mate Gorbe, Mária Kovács, Ede Migh, Allen Goodman, Tamás Balassa, Krisztián Koós, , Péter Horváth

The paper introduces a deep learning framework for nucleus segmentation that uses image style transfer to adapt to new data without expert annotations, outperforming existing methods on diverse microscopy images.

Cell Systems · May 1, 2020Peer-reviewedBioinformatics

Test-time augmentation for deep learning-based cell segmentation on microscopy images

Nikita Moshkov, Botond Mathe, Attila Kertész‐Farkas, Réka Hollandi, Péter Horváth

This paper applies test-time augmentation to improve cell segmentation accuracy in microscopy images using U-Net and Mask R-CNN models, achieving a better score in the DSB 2018 competition.

Scientific Reports · Mar 19, 2020Peer-reviewedBioinformatics