| Digital rock physics benchmarks—Part I: Imaging and segmentation H Andrä, N Combaret, J Dvorkin, E Glatt, J Han, M Kabel, Y Keehm, ... Computers & Geosciences 50, 25-32, 2013 | 675 | 2013 |
| Digital rock physics benchmarks—Part II: Computing effective properties H Andrä, N Combaret, J Dvorkin, E Glatt, J Han, M Kabel, Y Keehm, ... Computers & Geosciences 50, 33-43, 2013 | 582 | 2013 |
| Structural clusters of evolutionary trace residues are statistically significant and common in proteins S Madabushi, H Yao, M Marsh, DM Kristensen, A Philippi, ME Sowa, ... Journal of molecular biology 316 (1), 139-154, 2002 | 250 | 2002 |
| Application of deep learning convolutional neural networks for internal tablet defect detection: high accuracy, throughput, and adaptability X Ma, N Kittikunakorn, B Sorman, H Xi, A Chen, M Marsh, A Mongeau, ... Journal of Pharmaceutical Sciences 109 (4), 1547-1557, 2020 | 43 | 2020 |
| Dragonfly as a platform for easy image-based deep learning applications R Makovetsky, N Piche, M Marsh Microscopy and microanalysis 24 (S1), 532-533, 2018 | 43 | 2018 |
| X-ray CT and laboratory measurements on glacial till subsoil cores: assessment of inherent and compaction-affected soil structure characteristics M Lamandé, D Wildenschild, FE Berisso, A Garbout, M Marsh, P Moldrup, ... Soil Science 178 (7), 359-368, 2013 | 43 | 2013 |
| Automated segmentation of computed tomography images of fiber-reinforced composites by deep learning A Badran, D Marshall, Z Legault, R Makovetsky, B Provencher, N Piché, ... Journal of Materials Science 55, 16273-16289, 2020 | 41 | 2020 |
| Steps toward automated deprocessing of integrated circuits EL Principe, N Asadizanjani, D Forte, M Tehranipoor, R Chivas, ... ISTFA 2017: Proceedings from the 43rd International Symposium for Testing …, 2017 | 32 | 2017 |
| Correlative X-ray and electron microscopy for multi-scale characterization of heterogeneous shale reservoir pore systems J Goral, I Miskovic, J Gelb, M Marsh AAPG Special Volumes, 2016 | 16 | 2016 |
| Poromechanics investigation at pore-scale using digital rock physics laboratory S Zhang, N Saxena, P Barthelemy, M Marsh, G Mavko, T Mukerji Proc., The Proceedings of 2011 COMSOL Conference in Stuttgart, 2011 | 13 | 2011 |
| Deep learning convolutional neural networks for pharmaceutical tablet defect detection X Ma, N Kittikunakorn, B Sorman, H Xi, A Chen, M Marsh, A Mongeau, ... Microscopy and Microanalysis 26 (S2), 1606-1609, 2020 | 10 | 2020 |
| Simplifying and streamlining large-scale materials image processing with wizard-driven and scalable deep learning B Provencher, N Piché, M Marsh Microscopy and Microanalysis 25 (S2), 402-403, 2019 | 8 | 2019 |
| Dragonfly SegmentationTrainer-A General and User-Friendly Machine Learning Image Segmentation Solution N Piche, I Bouchard, M Marsh Microscopy and Microanalysis 23 (S1), 132-133, 2017 | 8 | 2017 |
| Processing of micro-CT images of granodiorite rock samples using convolutional neural networks (CNN), Part I: Super-resolution enhancement using a 3D CNN A Roslin, M Marsh, N Piche, B Provencher, TR Mitchell, IA Onederra, ... Minerals Engineering 188, 107748, 2022 | 7 | 2022 |
| Forget about cleaning up your micrographs: deep learning segmentation is robust to image artifacts P Dong, B Provencher, N Basim, N Piché, M Marsh Microscopy and Microanalysis 26 (S2), 1468-1469, 2020 | 7 | 2020 |
| Automated voice system and method H Hutchinson, M Marsh, W McMaster US Patent App. 12/190,643, 2010 | 5 | 2010 |
| Dragonfly as a Flexible Platform for Interpreting and Processing Hyperspectral and other High-dimensional Images N Piche, F Cote, E Yen, M Marsh Microscopy and Microanalysis 24 (S1), 560-561, 2018 | 4 | 2018 |
| Deep Learning-Based Segmentation of Cryo-Electron Tomograms JE Heebner, C Purnell, RK Hylton, M Marsh, MA Grillo, MT Swulius JoVE (Journal of Visualized Experiments), e64435, 2022 | 3 | 2022 |
| Phantoms Improve Robustness of Deep Learning Automated Segmentation in Cryotomography J Heebner, C Purnell, M Marsh, M Swulius Microscopy and Microanalysis 28 (S1), 1226-1228, 2022 | 2 | 2022 |
| Workflow Automation and Portability Enable High Throughput Image Processing and Segmentation for Cell Biology Systems B Provencher, R Makovetsky, E Yen, N Piché, M Marsh Microscopy and Microanalysis 25 (S2), 1388-1389, 2019 | 2 | 2019 |
