Mike Marsh

1.9k total citations · 2 hit papers
32 papers, 1.4k citations indexed

About

Mike Marsh is a scholar working on Structural Biology, Surfaces, Coatings and Films and Biomedical Engineering. According to data from OpenAlex, Mike Marsh has authored 32 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Structural Biology, 9 papers in Surfaces, Coatings and Films and 5 papers in Biomedical Engineering. Recurrent topics in Mike Marsh's work include Advanced Electron Microscopy Techniques and Applications (10 papers), Electron and X-Ray Spectroscopy Techniques (9 papers) and Machine Learning in Materials Science (5 papers). Mike Marsh is often cited by papers focused on Advanced Electron Microscopy Techniques and Applications (10 papers), Electron and X-Ray Spectroscopy Techniques (9 papers) and Machine Learning in Materials Science (5 papers). Mike Marsh collaborates with scholars based in Canada, United States and Australia. Mike Marsh's co-authors include Youngseuk Keehm, Erik Glatt, Tapan Mukerji, Minhui Lee, Nicolas Combaret, Andreas Wiegmann, Fabian Krzikalla, Nishank Saxena, Xin Zhan and Heiko Andrä and has published in prestigious journals such as Journal of Materials Science, Journal of Pharmaceutical Sciences and Soil Science.

In The Last Decade

Mike Marsh

30 papers receiving 1.4k citations

Hit Papers

Digital rock physics benchmarks—Part I: Imaging and segme... 2012 2026 2016 2021 2012 2012 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Digital rock physics benchmarks—Part I: Imaging and segmentation
    2012 552 citations Heiko Andrä, Nicolas Combaret et al. Computers & Geosciences profile →
  2. Digital rock physics benchmarks—part II: Computing effective properties
    2012 460 citations Heiko Andrä, Nicolas Combaret et al. Computers & Geosciences profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mike Marsh Canada 12 715 555 457 328 194 32 1.4k
Erik Glatt Germany 12 724 1.0× 544 1.0× 413 0.9× 302 0.9× 167 0.9× 33 1.3k
Robert Sok Australia 18 1.1k 1.5× 921 1.7× 568 1.2× 250 0.8× 326 1.7× 40 1.6k
Shane Latham Australia 18 463 0.6× 447 0.8× 321 0.7× 160 0.5× 125 0.6× 53 1.2k
Nishank Saxena United States 20 1.3k 1.9× 1.0k 1.9× 840 1.8× 682 2.1× 308 1.6× 52 2.1k
Matthias Kabel Germany 18 731 1.0× 1.4k 2.6× 659 1.4× 326 1.0× 167 0.9× 37 2.2k
James E. McClure United States 27 1.2k 1.6× 656 1.2× 579 1.3× 147 0.4× 584 3.0× 77 1.9k
Holger Averdunk Australia 15 515 0.7× 498 0.9× 330 0.7× 119 0.4× 140 0.7× 22 1.2k
Kirill M. Gerke Russia 23 738 1.0× 813 1.5× 533 1.2× 96 0.3× 432 2.2× 81 1.8k
Pierre Bésuelle France 21 486 0.7× 1.2k 2.2× 308 0.7× 350 1.1× 153 0.8× 43 2.2k
Trond Varslot Australia 20 397 0.6× 565 1.0× 238 0.5× 159 0.5× 107 0.6× 59 1.4k

Countries citing papers authored by Mike Marsh

Since Specialization
Citations

This map shows the geographic impact of Mike Marsh'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 Mike Marsh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mike Marsh more than expected).

Fields of papers citing papers by Mike Marsh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mike Marsh. 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 Mike Marsh. The network helps show where Mike Marsh may publish in the future.

Co-authorship network of co-authors of Mike Marsh

This figure shows the co-authorship network connecting the top 25 collaborators of Mike Marsh. A scholar is included among the top collaborators of Mike Marsh 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 Mike Marsh. Mike Marsh 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.
2.
Kar, Deepayan, Yeon Jin Kim, Orin Packer, et al.. (2023). Volumetric Reconstruction of a Human Retinal Pigment Epithelial Cell Reveals Specialized Membranes and Polarized Distribution of Organelles. Investigative Ophthalmology & Visual Science. 64(15). 35–35. 21 indexed citations
3.
4.
Marsh, Mike, et al.. (2022). Deep Learning-Based Segmentation of Cryo-Electron Tomograms. Journal of Visualized Experiments. 19 indexed citations
5.
6.
Piché, Nicolas, et al.. (2021). Centralizing digital resources for data management, processing, and analysis for enterprise scale imaging research. Microscopy and Microanalysis. 27(S1). 1084–1085. 6 indexed citations
7.
Ma, Xiangyu, Hanmi Xi, Antong Chen, et al.. (2020). Application of Deep Learning Convolutional Neural Networks for Internal Tablet Defect Detection: High Accuracy, Throughput, and Adaptability. Journal of Pharmaceutical Sciences. 109(4). 1547–1557. 68 indexed citations
8.
Marshall, David B., et al.. (2020). Automated segmentation of computed tomography images of fiber-reinforced composites by deep learning. Journal of Materials Science. 55(34). 16273–16289. 73 indexed citations
9.
Piché, Nicolas, et al.. (2020). Forget About Cleaning up Your Micrographs: Deep Learning Segmentation is Robust to Image Artifacts. Microscopy and Microanalysis. 26(S2). 1468–1469. 6 indexed citations
10.
Gauvin, Raynald, et al.. (2019). Extending Monte Carlo Simulations of Electron Microscopy Images and Hyperspectral Images in a User-Friendly Framework. Microscopy and Microanalysis. 25(S2). 222–223. 1 indexed citations
11.
Marsh, Mike, et al.. (2019). SC-1 Introduction to practical AI image processing and analysis without programming. Microscopy. 68(Supplement_1). i11–i11. 1 indexed citations
12.
Piché, Nicolas, et al.. (2019). Simplifying and Streamlining Large-Scale Materials Image Processing with Wizard-Driven and Scalable Deep Learning. Microscopy and Microanalysis. 25(S2). 402–403. 8 indexed citations
13.
Piché, Nicolas, et al.. (2018). Survey of Image Analysis Methods Applied to Consumer Foods. Microscopy and Microanalysis. 24(S1). 1208–1209.
14.
Piché, Nicolas, et al.. (2018). Dragonfly as a Platform for Easy Image-based Deep Learning Applications. Microscopy and Microanalysis. 24(S1). 532–533. 54 indexed citations
15.
Asadizanjani, Navid, Domenic Forte, Mark Tehranipoor, et al.. (2017). Steps Toward Automated Deprocessing of Integrated Circuits. Proceedings - International Symposium for Testing and Failure Analysis. 81504. 285–298. 18 indexed citations
16.
Andrew, Matthew, et al.. (2016). Non-Invasive Multi-Scale Imaging and Modelling Using X-Ray Microscopy. Microscopy and Microanalysis. 22(S3). 108–109. 2 indexed citations
17.
Andrä, Heiko, Nicolas Combaret, Jack Dvorkin, et al.. (2012). Digital rock physics benchmarks—Part I: Imaging and segmentation. Computers & Geosciences. 50. 25–32. 552 indexed citations breakdown →
18.
Andrä, Heiko, Nicolas Combaret, Jack Dvorkin, et al.. (2012). Digital rock physics benchmarks—part II: Computing effective properties. Computers & Geosciences. 50. 33–43. 460 indexed citations breakdown →
19.
Marsh, Mike, et al.. (2005). Mr T.: Automated Electron Cryotomography for JEOL 2010F TEM. Microscopy and Microanalysis. 11(S02). 1 indexed citations
20.
Marsh, Mike, et al.. (1972). A pseudoperceptual display system for investigating human statistical decision processes. Behavior Research Methods. 4(1). 1–2. 1 indexed citations

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Erik Glatt Breakdown of academic impact, for papers by Robert Sok Breakdown of academic impact, for papers by Shane Latham Breakdown of academic impact, for papers by Nishank Saxena Breakdown of academic impact, for papers by Matthias Kabel Breakdown of academic impact, for papers by James E. McClure Breakdown of academic impact, for papers by Holger Averdunk Breakdown of academic impact, for papers by Kirill M. Gerke Breakdown of academic impact, for papers by Pierre Bésuelle Breakdown of academic impact, for papers by Trond Varslot
Rankless by CCL
2026