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Please see below for selected publications from the TouchLab group.
2021
Neary-Zajiczek, et al. Stain-free identification of tissue pathology using a generative adversarial network to infer nanomechanical signatures, Nanoscale Adv. (2021)
Bendkowski, C., et al., Autonomous object harvesting using synchronized optoelectronic microrobots, arXiv:2103.04912 (2021)
Shaw, M., et al., Optical mesoscopy, machine learning and computational microscopy enable high information content diagnostic imaging of blood films, J. Pathol., 255: 62-71 (2021)
2020
Claveau, R., et al., Structure-dependent Amplification for Denoising and Background Correction in Fourier Ptychographic Microscopy, Opt. Express, 28(4), 35438-35453 (2020)
Manescu, P. et al., A weakly supervised deep learning approach for detecting malaria and sickle cells in blood films, In: Martel A.L. et al. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. MICCAI 2020. Lecture Notes in Computer Science, vol 12265. Springer, Cham.
Essmann, C. et al., Mechanical properties measured by atomic force microscopy define health biomarkers in ageing C. elegans, Nat. Commun. 11, 1043 (2020)
Manescu, P. et al., Expert‐level automated malaria diagnosis on routine blood films with deep neural networks, Am. J. Hematol. 95: 883-891 (2020)
Claveau, R. et al., Digital refocusing and extended depth of field reconstruction in Fourier ptychographic microscopy, Biomed. Opt. Express, 11(1), 215-226 (2020)
2019
Neary-Zajiczek, L. et al., Whole-Sample Mapping of Cancerous and Benign Tissue Properties, In: Shen D. et al. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science, vol 11764. Springer, Cham.
Sims, R. et al., Light field microscopy: principles and applications, infocus magazine (2019)
2018
Shaw, M. et al., Three-dimensional behavioural phenotyping of freely moving C. elegans using quantitative light field microscopy, PLOS ONE, 13(7), 14230-14244 (2018)
Essmann, C., Atomic Force Stiffness Imaging: Capturing differences in mechanical properties to identify and localize areas of prostate cancer tissue, Proc. SPIE 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 105761M (13 March 2018)
Osman, G. A., Natural Infection ofC. elegansby an OomyceteReveals a New Pathogen-Specific Immune Response, Curr. Biol., 28, 640-648 (2018)
2017
Elmi, M. et al., Determining the biomechanics of touch sensation in C. elegans, Sci. Rep., 7(1), 1-12 (2017)
Essmann, C. et al., In-vivo high resolution AFM topographic imaging of Caenorhabditis elegans reveals previously unreported surface structures of cuticle mutants, Nanomedicine, 13(1), 183-189 (2017)
2016
Shaw, M. et al., Investigation of mechanosensation in C. elegans using light field calcium imaging, Biomed. Opt. Express, 7(7), 2877-2887 (2016)
Zajiczek, L. et al., Nano-mechanical single-cell sensing of cell–matrix contacts, Nanoscale, 8(42), 18105-18112 (2016)