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Peter Horvarth

  • PL 20 (Tukholmankatu 8)

    00014

    Finland

20142020

Research output per year

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Personal profile

Fields of Science

  • 3111 Biomedicine

International and National Collaboration Publications and projects within past five years.

Publications

3D-Cell-Annotator: an open-source active surface tool for single-cell segmentation in 3D microscopy images

Tasnadi, E. A., Toth, T., Kovacs, M., Diosdi, A., Pampaloni, F., Molnar, J., Piccinini, F. & Horvath, P., 1 May 2020, In : Bioinformatics. 36, 9, p. 2948-2949 2 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
File

nucleAIzer: A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer

Hollandi, R., Szkalisity, A., Toth, T., Tasnadi, E., Molnar, C., Mathe, B., Grexa, I., Molnar, J., Balind, A., Gorbe, M., Kovacs, M., Migh, E., Goodman, A., Balassa, T., Koos, K., Wang, W., Caicedo, J. C., Bara, N., Kovacs, F., Paavolainen, L. & 5 others, Danka, T., Kriston, A., Carpenter, A. E., Smith, K. & Horvath, P., 20 May 2020, In : Cell Systems. 10, 5, p. 453-+ 12 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
File

Routing Nanomolar Protein Cargoes to Lipid Raft-Mediated/Caveolar Endocytosis through a Ganglioside GM1-Specific Recognition Tag

Imre, N., Hetenyi, A., Szabo, E., Bodnar, B., Szkalisity, A., Grof, I., Bocsik, A., Deli, M. A., Horvath, P., Czibula, A., Monostori, E. & Martinek, T. A., Feb 2020, In : Advanced Science. 7, 4, 10 p., 1902621.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
File

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

Moshkov, N., Mathe, B., Kertesz-Farkas, A., Hollandi, R. & Horvath, P., 19 Mar 2020, In : Scientific Reports. 10, 1

Research output: Contribution to journalArticleScientificpeer-review

Open Access
File

A Balanced Phase Field Model for Active Contours

Molnar, J., Tasnadi, E. & Horvath, P., 2019, Scale Space and Variational Methods in Computer Vision : 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 – July 4, 2019, Proceedings . Lellmann, J., Burger, M. & Modersitzki, J. (eds.). Cham: Springer Nature Switzerland, p. 419-431 13 p. (Lecture Notes in Computer Science ; vol. 11603).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Projects