Martin Maška

3.0k total citations
25 papers, 481 citations indexed

About

Martin Maška is a scholar working on Biophysics, Cell Biology and Molecular Biology. According to data from OpenAlex, Martin Maška has authored 25 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Biophysics, 9 papers in Cell Biology and 8 papers in Molecular Biology. Recurrent topics in Martin Maška's work include Cell Image Analysis Techniques (14 papers), Cellular Mechanics and Interactions (9 papers) and Advanced Fluorescence Microscopy Techniques (6 papers). Martin Maška is often cited by papers focused on Cell Image Analysis Techniques (14 papers), Cellular Mechanics and Interactions (9 papers) and Advanced Fluorescence Microscopy Techniques (6 papers). Martin Maška collaborates with scholars based in Czechia, Spain and Russia. Martin Maška's co-authors include Carlos Ortíz-de-Solórzano, Michal Kozubek, Pavel Matula, Ana Rouzaut, Arrate Muñoz‐Barrutia, Dmitry V. Sorokin, Carlos Castilla, Vendula Pospíchalová, Saray Garasa and Anna Kotrbová and has published in prestigious journals such as Bioinformatics, PLoS ONE and Scientific Reports.

In The Last Decade

Martin Maška

25 papers receiving 476 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Martin Maška Czechia 12 188 151 133 102 71 25 481
Kevan Shah United States 7 264 1.4× 210 1.4× 183 1.4× 55 0.5× 45 0.6× 7 546
Weimiao Yu Singapore 18 164 0.9× 341 2.3× 150 1.1× 84 0.8× 282 4.0× 36 913
Pavel Matula Czechia 18 174 0.9× 497 3.3× 52 0.4× 82 0.8× 39 0.5× 41 716
Douglas B. Wheeler United States 6 229 1.2× 583 3.9× 115 0.9× 31 0.3× 104 1.5× 7 841
Alexander S. Zhovmer United States 9 94 0.5× 254 1.7× 107 0.8× 24 0.2× 111 1.6× 16 517
Alberto Santamaría-Pang United States 13 120 0.6× 228 1.5× 50 0.4× 52 0.5× 28 0.4× 32 544
Minhyeok Kim South Korea 11 131 0.7× 131 0.9× 238 1.8× 60 0.6× 11 0.2× 28 578
Joe Chalfoun United States 11 223 1.2× 165 1.1× 110 0.8× 109 1.1× 22 0.3× 32 468
Felix Zhou United Kingdom 12 78 0.4× 355 2.4× 116 0.9× 37 0.4× 93 1.3× 26 638
Mika Kaakinen Finland 15 45 0.2× 224 1.5× 59 0.4× 33 0.3× 56 0.8× 41 539

Countries citing papers authored by Martin Maška

Since Specialization
Citations

This map shows the geographic impact of Martin Maška's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Martin Maška with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Maška more than expected).

Fields of papers citing papers by Martin Maška

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Maška. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Martin Maška. The network helps show where Martin Maška may publish in the future.

Co-authorship network of co-authors of Martin Maška

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Maška. A scholar is included among the top collaborators of Martin Maška based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Martin Maška. Martin Maška is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Koledová, Zuzana, et al.. (2022). Segmentation and Tracking of Mammary Epithelial Organoids in Brightfield Microscopy. IEEE Transactions on Medical Imaging. 42(1). 281–290. 12 indexed citations
2.
Paavolainen, Lassi, Volker Bäcker, Benjamin Pavie, et al.. (2020). BIAFLOWS: A Collaborative Framework to Reproducibly Deploy and Benchmark Bioimage Analysis Workflows. Patterns. 1(3). 100040–100040. 21 indexed citations
3.
Gómez‐de‐Mariscal, Estibaliz, Martin Maška, Anna Kotrbová, et al.. (2019). Deep-Learning-Based Segmentation of Small Extracellular Vesicles in Transmission Electron Microscopy Images. Scientific Reports. 9(1). 13211–13211. 43 indexed citations
4.
Maška, Martin, Tereza Nečasová, Dmitry V. Sorokin, et al.. (2019). Toward Robust Fully 3D Filopodium Segmentation and Tracking in Time-Lapse Fluorescence Microscopy. 819–823. 2 indexed citations
5.
Kotrbová, Anna, Martin Maška, Ladislav Ilkovics, et al.. (2019). TEM ExosomeAnalyzer: a computer‐assisted software tool for quantitative evaluation of extracellular vesicles in transmission electron microscopy images. Journal of Extracellular Vesicles. 8(1). 1560808–1560808. 51 indexed citations
6.
Sorokin, Dmitry V., Igor Peterlík, Vladimír Ulman, et al.. (2018). FiloGen: A Model-Based Generator of Synthetic 3-D Time-Lapse Sequences of Single Motile Cells With Growing and Branching Filopodia. IEEE Transactions on Medical Imaging. 37(12). 2630–2641. 19 indexed citations
7.
Castilla, Carlos, Martin Maška, Dmitry V. Sorokin, Erik Meijering, & Carlos Ortíz-de-Solórzano. (2018). 3-D Quantification of Filopodia in Motile Cancer Cells. IEEE Transactions on Medical Imaging. 38(3). 862–872. 14 indexed citations
8.
Castilla, Carlos, Martin Maška, Cristina Ederra, et al.. (2017). Characterization of three-dimensional cancer cell migration in mixed collagen-Matrigel scaffolds using microfluidics and image analysis. PLoS ONE. 12(2). e0171417–e0171417. 113 indexed citations
9.
Maška, Martin & Pavel Matula. (2017). Particle Tracking Accuracy Measurement Based on Comparison of Linear Oriented Forests. 11–17. 3 indexed citations
10.
Sorokin, Dmitry V., Igor Peterlík, Vladimír Ulman, David Svoboda, & Martin Maška. (2017). Model-based generation of synthetic 3D time-lapse sequences of motile cells with growing filopodia. 822–826. 4 indexed citations
11.
Matula, Pavel, et al.. (2015). Cell Tracking Accuracy Measurement Based on Comparison of Acyclic Oriented Graphs. PLoS ONE. 10(12). e0144959–e0144959. 51 indexed citations
12.
Maška, Martin, et al.. (2015). Quantification of the 3D collagen network geometry in confocal reflection microscopy. 1791–1794. 5 indexed citations
13.
Castilla, Carlos, Martin Maška, Cristina Ederra, et al.. (2015). Characterization of the role of collagen network structure and composition in cancer cell migration. PubMed. 2015. 8139–8142. 5 indexed citations
14.
Maška, Martin, et al.. (2013). Segmentation and Shape Tracking of Whole Fluorescent Cells Based on the Chan–Vese Model. IEEE Transactions on Medical Imaging. 32(6). 995–1006. 66 indexed citations
15.
Matula, Pavel, et al.. (2012). Smooth Chan–Vese segmentation via graph cuts. Pattern Recognition Letters. 33(10). 1405–1410. 11 indexed citations
16.
Maška, Martin, Arrate Muñoz‐Barrutia, & Carlos Ortíz-de-Solórzano. (2012). Fast tracking of fluorescent cells based on the Chan-Vese model. 1316–1319. 5 indexed citations
17.
Maška, Martin, Pavel Matula, & Michal Kozubek. (2011). Simultaneous Tracking of Multiple Objects Using Fast Level Set-Like Algorithm. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 16. 117–125. 2 indexed citations
18.
Maška, Martin, et al.. (2011). A Simple Topology Preserving Max-Flow Algorithm for Graph Cut Based Image Segmentation. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 16. 25. 2 indexed citations
19.
Stejskal, Stanislav, et al.. (2010). The role of chromatin condensation during granulopoiesis in the regulation of gene cluster expression. Epigenetics. 5(8). 758–766. 6 indexed citations
20.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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