Nicolas Piché

816 total citations
40 papers, 553 citations indexed

About

Nicolas Piché is a scholar working on Surfaces, Coatings and Films, Structural Biology and Biomedical Engineering. According to data from OpenAlex, Nicolas Piché has authored 40 papers receiving a total of 553 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Surfaces, Coatings and Films, 10 papers in Structural Biology and 10 papers in Biomedical Engineering. Recurrent topics in Nicolas Piché's work include Electron and X-Ray Spectroscopy Techniques (11 papers), Advanced Electron Microscopy Techniques and Applications (10 papers) and Machine Learning in Materials Science (9 papers). Nicolas Piché is often cited by papers focused on Electron and X-Ray Spectroscopy Techniques (11 papers), Advanced Electron Microscopy Techniques and Applications (10 papers) and Machine Learning in Materials Science (9 papers). Nicolas Piché collaborates with scholars based in Canada, United States and South Africa. Nicolas Piché's co-authors include Mike Marsh, Claude Kauffmann, Christopher Pal, Samuel Kadoury, Natalie Reznikov, Marc D. McKee, David B. Marshall, Daniel Skomski, Xiangyu Ma and Antong Chen and has published in prestigious journals such as Journal of Materials Science, Journal of Pharmaceutical Sciences and Materials Science and Engineering C.

In The Last Decade

Nicolas Piché

32 papers receiving 528 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicolas Piché Canada 14 125 122 98 68 66 40 553
Liwei Deng China 16 111 0.9× 157 1.3× 63 0.6× 61 0.9× 49 0.7× 87 698
Yutong Liu China 17 205 1.6× 107 0.9× 73 0.7× 183 2.7× 35 0.5× 91 949
Xingdong Li China 15 140 1.1× 91 0.7× 143 1.5× 103 1.5× 61 0.9× 67 672
Boyuan Ma China 10 77 0.6× 233 1.9× 81 0.8× 23 0.3× 98 1.5× 23 516
Seongjin Park South Korea 11 83 0.7× 201 1.6× 60 0.6× 30 0.4× 35 0.5× 57 702
Yang Huang China 12 74 0.6× 57 0.5× 123 1.3× 43 0.6× 55 0.8× 51 482
Liming Zhao China 13 83 0.7× 199 1.6× 157 1.6× 57 0.8× 123 1.9× 32 565
Yuqian Zhao China 13 197 1.6× 55 0.5× 91 0.9× 98 1.4× 60 0.9× 56 518
Yudan Wang China 11 82 0.7× 128 1.0× 56 0.6× 35 0.5× 40 0.6× 37 561

Countries citing papers authored by Nicolas Piché

Since Specialization
Citations

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

Fields of papers citing papers by Nicolas Piché

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicolas Piché

This figure shows the co-authorship network connecting the top 25 collaborators of Nicolas Piché. A scholar is included among the top collaborators of Nicolas Piché 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 Nicolas Piché. Nicolas Piché 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
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Piché, Nicolas, et al.. (2025). Accurate Reconstruction of Gas Turbine Blade Geometry Using 3D/2D Rigid-Registration and CT View Optimization. e-Journal of Nondestructive Testing. 30(2).
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Piché, Nicolas, et al.. (2024). Optimizing SEM parameters for segmentation with AI – Part 2: Designing and training a regression model. Computational Materials Science. 245. 113283–113283.
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Piché, Nicolas, et al.. (2024). Workflow automation of SEM acquisitions and feature tracking. Ultramicroscopy. 269. 114093–114093.
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Piché, Nicolas, et al.. (2024). Optimizing SEM parameters for segmentation with AI – Part 1: Generating a training set. Computational Materials Science. 245. 113255–113255.
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Desrosiers, Catherine, Morgan Letenneur, Fabrice Bernier, et al.. (2024). Automated porosity segmentation in laser powder bed fusion part using computed tomography: a validity study. Journal of Intelligent Manufacturing. 36(2). 1341–1361. 11 indexed citations
8.
Plessis, Anton du, Catherine Desrosiers, Marta Majkut, et al.. (2023). X-ray tomography study of “squeezed pores” in additively manufactured titanium alloy subjected to hot isostatic pressing. e-Journal of Nondestructive Testing. 28(3). 1 indexed citations
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Piché, Nicolas, et al.. (2023). Automated SEM Acquisitions and Segmentation With AI. Microscopy and Microanalysis. 29(Supplement_1). 458–459. 1 indexed citations
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Desrosiers, Catherine, Morgan Letenneur, Fabrice Bernier, et al.. (2022). Correlative Laser Confocal Microscopy Study and Multimodal 2D/3D Registration as Ground Truth for X-ray Inspection of Internal Defects in LPBF Manufacturing. e-Journal of Nondestructive Testing. 27(3). 7 indexed citations
12.
Aydin, Roland C., Yong Li, Nicolas Piché, et al.. (2022). Training Deep Neural Networks to Reconstruct Nanoporous Structures From FIB Tomography Images Using Synthetic Training Data. Frontiers in Materials. 9. 14 indexed citations
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Alsheghri, Ammar, Natalie Reznikov, Nicolas Piché, et al.. (2021). Optimization of 3D network topology for bioinspired design of stiff and lightweight bone-like structures. Materials Science and Engineering C. 123. 112010–112010. 22 indexed citations
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Reznikov, Natalie, et al.. (2020). Deep learning for 3D imaging and image analysis in biomineralization research. Journal of Structural Biology. 212(1). 107598–107598. 24 indexed citations
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Reznikov, Natalie, Ammar Alsheghri, Nicolas Piché, et al.. (2020). Altered topological blueprint of trabecular bone associates with skeletal pathology in humans. Bone Reports. 12. 100264–100264. 14 indexed citations
16.
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
17.
Kauffmann, Claude, An Tang, Olivier P. Thomas, et al.. (2014). Impact of contrast injection and stent-graft implantation on reproducibility of volume measurements in semiautomated segmentation of abdominal aortic aneurysm on computed tomography. European Radiology. 24(7). 1594–1601. 7 indexed citations
18.
Kauffmann, Claude, Josée Dubois, Asmaa Mansour, et al.. (2013). Clinical validation of semi-automated software for volumetric and dynamic contrast enhancement analysis of soft tissue venous malformations on Magnetic Resonance Imaging examination. European Radiology. 24(2). 542–551. 14 indexed citations
19.
Kauffmann, Claude & Nicolas Piché. (2009). Seeded ND medical image segmentation by cellular automaton on GPU. International Journal of Computer Assisted Radiology and Surgery. 5(3). 251–262. 37 indexed citations
20.
Kauffmann, Claude & Nicolas Piché. (2008). Cellular automaton for ultra-fast watershed transform on GPU. Proceedings - International Conference on Pattern Recognition. 1–4. 19 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.

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