Nanomotion
Nanomotion is a project that merges AI with nanoscopy. It aims to study the motion of vesicles at a nanoscale using classification algorithms based on CNN.
K. Agarwal and D.K. Prasad, “Eigen-analysis reveals components supporting super-resolution imaging of blinking fluorophores”, Scientific Reports, vol. 7, 2017. (impact factor = 4.259) (Source code)(PDF)
K. Agarwal, R. Machan, and D. K. Prasad, “Non-heuristic automatic techniques for overcoming low signal-to-noise-ratio bias of localization microscopy and multiple signal classification algorithm”, Scientific Reports, 2018. (impact factor = 4.259)(source code and PDF)
K. Samanta, J. Joseph, B. S. Ahluwalia, K. Agarwal. “Study of electric fields of diffraction from spatial light modulator: Discussion”. Optical Society of America. Journal A: Optics, Image Science, and Vision; Volume 36.(10) p. 1778-1786 (2019) (PDF)
I. S. Opstad, F. Ströhl, Å. B. Birgisdottir, S. A. Acuña M., T. Kalstad, T. Myrmel, K. Agarwal and B. S. Ahluwalia, “Adaptive fluctuation imaging captures rapid subcellular dynamics”, Proc. SPIE 11076, Advances in Microscopic Imaging II, 110761W (22 July 2019) (PDF)
S. Acuña M., F. Ströhl, I. S. Opstad, B. S. Ahluwalia and K. Agarwal. “MusiJ: an ImageJ plugin for video nanoscopy.” Biomed. Opt. Express 11, 2548-2559 (2020) (PDF)
A. Ahmed, I. S. Opstad, Å. B. Birgisdottir, T. Myrmel, B. S. Ahluwalia, K. Agarwal and D. K. Prasad, “Learning nanoscale motion patterns of vesicles in living cells”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, Washington, USA, 16-18, June, 2020.
F. Ströhl, S. Jadhav, B. S. Ahluwalia, K. Agarwal, and D. K. Prasad, “Object detection neural network improves Fourier ptychography reconstruction,” Opt. Express 28, 37199-37208 (2020) (PDF)
N. Jayakumar, Ø. I. Helle, K. Agarwal, and B. S. Ahluwalia, “On-chip TIRF nanoscopy by applying Haar wavelet kernel analysis on intensity fluctuations induced by chip illumination,” Opt. Express 28, 35454-35468 (2020) (PDF)
S. Acuña, I. S. Opstad, F. Godtliebsen, B. S. Ahluwalia, and K. Agarwal, “Soft thresholding schemes for multiple signal classification algorithm,” Opt. Express 28, 34434-34449 (2020) (PDF)
L. Zhang, X. Kuiwen, Y. Zhong, and K. Agarwal. “Solving Phaseless Highly Nonlinear Inverse Scattering Problems With Contraction Integral Equation for Inversion.” IEEE Transactions on Computational Imaging 6 (2020): 1106-1116. (PDF)
F. Ströhl, S. Jadhav, B. S. Ahluwalia, K. Agarwal, and D. K. Prasad, “Object detection neural network improves Fourier ptychography reconstruction,” Opt. Express 28, 37199-37208 (2020). (PDF)
S. Jadhav, S. Acuña, I. S. Opstad, B. S. Ahluwalia, K. Agarwal, and D. K. Prasad, “Artefact removal in ground truth deficient fluctuations-based nanoscopy images using deep learning,” Biomed. Opt. Express 12, 191-210 (2021). (PDF)
S. Acuna, M. Roy, L. V. Hernández, V. K. Dubey, B. S. Ahluwalia, K. Agarwal, “Deriving high contrast fluorescence microscopy images through low contrast noisy image stacks,” Biomed. Opt. Express (2021). (PDF)
I.S. Opstad, D. H. Hansen, S. Acuña, F Ströhl, A Priyadarshi, J.-C. Tinguely, F. T. Dullo, R. A. Dalmo, T. Seternes, B. S. Ahluwalia, K. Agarwal, “Fluorescence fluctuation-based super-resolution microscopy using multimodal waveguided illumination,” Opt. Express (2021). (PDF)
Q. Do, S. Acuña, J. I. Kristiansen, K. Agarwal, P. H. Ha, “Highly Efficient and Scalable Framework for High-Speed Super-Resolution Microscopy,” IEEE Access (2021).(PDF)
K. Samanta, S. Sarkar, S. Acuña, J. Joseph, B. S. Ahluwalia, K. Agarwal, “Blind Super-Resolution Approach for Exploiting Illumination Variety in Optical-Lattice Illumination Microscopy,” ACS Photonics (2021).(PDF)
L.E. V. Hernández, V. K. Dubey, M. Nystad, Jean-Claude Tinguely, D. A .Coucheron, F. T. Dullo, A. Priyadarshi, S. Acuña, J. M. Mateos, G. Barmettler, U. Ziegler, A.M. K. Hovd, K. A. Fenton, G.Acharya, K. Agarwal, B. S. Ahluwalia, “Photonic chip-based multimodal super-resolution microscopy for histopathological assessment of cryopreserved tissue sections,” bioRxiv (2021). (PDF)
[J19] A. Somani, A. A. Sekh, I. S. Opstad, Å. B. Birgisdottir, T. Myrmel, B. S. Ahluwalia, K. Agarwal, D. K Prasad, A. Horsch, “Digital Staining of Mitochondria in Label-free Live-cell Microscopy,” Image processing for medicine (2021).(PDF)
[J20] A.A. Sekh, I. S. Opstad, G. Godtliebsen, Å.B. Birgisdottir, B.S. Ahluwalia, K. Agarwal, and D. K. Prasad, “Physics-based machine learning for subcellular segmentation in living cells” Nature Machine Intelligence (2021).(PDF)
[J21]S. Bhatt, A. Butola, A. Kumar, P. Thapa, A. Joshi, N. Singh, K. Agarwal, and D.S. Mehta, ” Single-shot multispectral quantitative phase imaging using deep neural network,”(2022) (PDF)
[J22] I. S. Opstad, G.Godtliebsen, B.S. Ahluwalia, T. Myrmel, K. Agarwal, and Å. B. Birgisdottir, “Mitochondrial dynamics and quantification of mitochondria‐derived vesicles in cardiomyoblasts using structured illumination microscopy.” Journal of Biophotonics (2022) (PDF).
[J23] L. Zicheng, M. Roy, D. K. Prasad, and K. Agarwal “Physics-guided loss functions improve deep learning performance in inverse scattering” IEEE Transactions on Computational Imaging (2022)(PDF).
[J24] A. Somani, A. A. Sekh, I. S. Opstad, Å. B. Birgisdottir, T. Myrmel, B.S. Ahluwalia, A. Horsch, K. Agarwal, and D. K. Prasad”Virtual labeling of mitochondria in living cells using correlative imaging and physics-guided deep learning” Biomedical Optics Express (2022)(PDF).
[J25] A. Butola, S. Acuna, D. H. Hansen, K. Agarwal “Scalable-resolution structured illumination microscopy” Optics Express (2022)(PDF).
[J26]A. Somani, P. Banerjee, M. Rastogi, K. Agarwal, D. K. Prasad, and A. Habib. “Image Inpainting With Hypergraphs for Resolution Improvement in Scanning Acoustic Microscopy.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, (2023).(PDF)
[J27] A. R. Punnakkal, S. S Jadhav, A. Horsch, K. Agarwal, D. K. Prasad, ” MiShape: 3D Shape Modelling of Mitochondria in Microscopy.” arXiv (2023) (PDF)
[J28] A. R. Punnakkal, G. Godtliebsen, A. Somani, S. A. A. Maldonado, Å. B. Birgisdottir, D. K. Prasad, A. Horsch, and K. Agarwal “Analyzing Mitochondrial Morphology Through Simulation Supervised Learning.” JoVE (Journal of Visualized Experiments) (2023).(PDF)
[J29] P. Banerjee, S. Mishra, N. Yadav, K. Agarwal, F. Melandsø, D. K. Prasad, and A. Habib. “Image inpainting in acoustic microscopy.” AIP Advances (2023). (PDF)
[J30] Y. Qin, A. Butola, and K. Agarwal “3D full-wave multi-scattering forward solver for coherent microscopes.” Optics Express (2023). (PDF)
[J31] S. Bhatt, A. Butola, A. Kumar, P. Thapa, A. Joshi, S. Jadhav, N. Singh, D. K. Prasad, K. Agarwal, D. S. Mehta, “Single-shot multispectral quantitative phase imaging of biological samples using deep learning”. Applied Optics (2023). (PDF)
[J32] G. Arora, A. Butola, R. Rajput, R. Agarwal, K. Agarwal, A. Horsch, D. K. Prasad, P. Senthilkumaran, “Taxonomy of hybridly polarized Stokes vortex beams”. arXiv (2023). (PDF)
[J33] G. Godtliebsen, K.B. Larsen, Z. Bhujabal, I. S. Opstad, M. Nager, A. R. Punnakkal, T. B. Kalstad, R. Olsen, T. Lund, D. K. Prasad, K. Agarwal, T. Myrmel, A. B. Birgisdottir, “High-resolution visualization and assessment of basal and OXPHOS-induced mitophagy in H9c2 cardiomyoblasts”. Autophagy (2023). (PDF)