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.
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.
Multiple signal classification algorithm for super-resolution fluorescence microscopy
K. Agarwal and R. Machan
Nature Communications, vol. 7, article id. 13752, 2016. (impact factor = 12.124)
Nature Paper: https://www.nature.com/articles/ncomms13752
Eigen-analysis reveals components
supporting super-resolution
imaging of blinking fluorophores
K. Agarwal and D.K. Prasad,
Scientific Reports, vol. 7, 2017. (impact factor = 4.259)
Source code: https://drive.google.com/file/d/0B10RxHxW3I92VkJfSmw4ZGtiQWs/view?usp=sharing
Non-heuristic automatic techniques for overcoming low signal-to-noise-ratio bias of localization microscopy and multiple signal classification algorithm
K. Agarwal, R. Machan, and D. K. Prasad
Scientific Reports 8, 4988 (2018). https://doi.org/10.1038/s41598-018-23374-7. (impact factor = 4.259)
Study of electric fields of diffraction from spatial light modulator: Discussion
K. Samanta, J. Joseph, B. S. Ahluwalia, K. Agarwal.
Optical Society of America. Journal A: Optics, Image Science, and Vision; Volume 36.(10) p. 1778-1786 (2019)
MusiJ: an ImageJ plugin for video nanoscopy
S. Acuña M., F. Ströhl, I. S. Opstad, B. S. Ahluwalia and K. Agarwal
Biomed. Opt. Express 11, 2548-2559 (2020)
Object detection neural network improves Fourier ptychography reconstruction
F. Ströhl, S. Jadhav, B. S. Ahluwalia, K. Agarwal, and D. K. Prasad
Opt. Express 28, 37199-37208 (2020)
On-chip TIRF nanoscopy by applying Haar wavelet kernel analysis on intensity fluctuations induced by chip illumination
N. Jayakumar, Ø. I. Helle, K. Agarwal, and B. S. Ahluwalia
Opt. Express 28, 35454-35468 (2020)
Soft thresholding schemes for multiple signal classification algorithm
S. Acuña, I. S. Opstad, F. Godtliebsen, B. S. Ahluwalia, and K. Agarwal
Opt. Express 28, 34434-34449 (2020)
Solving Phaseless Highly Nonlinear Inverse Scattering Problems With Contraction Integral Equation for Inversion
L. Zhang, X. Kuiwen, Y. Zhong, and K. Agarwal
IEEE Transactions on Computational Imaging 6 (2020): 1106-1116
Artefact removal in ground truth deficient fluctuations-based nanoscopy images using deep learning
S. Jadhav, S. Acuña, I. S. Opstad, B. S. Ahluwalia, K. Agarwal, and D. K. Prasad
Biomed. Opt. Express 12, 191-210 (2021). (PDF)
Deriving high contrast fluorescence microscopy images through low contrast noisy image stacks
S. Acuna, M. Roy, L. V. Hernández, V. K. Dubey, B. S. Ahluwalia, K. Agarwal
Biomed. Opt. Express (2021)
Fluorescence fluctuation-based super-resolution microscopy using multimodal waveguided illumination
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
Opt. Express (2021)
Highly Efficient and Scalable Framework for High-Speed Super-Resolution Microscopy
Q. Do, S. Acuña, J. I. Kristiansen, K. Agarwal, P. H. Ha
IEEE Access (2021)
Blind Super-Resolution Approach for Exploiting Illumination Variety in Optical-Lattice Illumination Microscopy
K. Samanta, S. Sarkar, S. Acuña, J. Joseph, B. S. Ahluwalia, K. Agarwal
ACS Photonics (2021)
Photonic chip-based multimodal super-resolution microscopy for histopathological assessment of cryopreserved tissue sections
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
bioRxiv (2021). (PDF)
Digital Staining of Mitochondria in Label-free Live-cell Microscopy
A. Somani, A. A. Sekh, I. S. Opstad, Å. B. Birgisdottir, T. Myrmel, B. S. Ahluwalia, K. Agarwal, D. K Prasad, A. Horsch
Image processing for medicine (2021).(PDF)
Physics-based machine learning for subcellular segmentation in living cells
A.A. Sekh, I. S. Opstad, G. Godtliebsen, Å.B. Birgisdottir, B.S. Ahluwalia, K. Agarwal, and D. K. Prasad
Nature Machine Intelligence (2021)
Mitochondrial dynamics and quantification of mitochondria‐derived vesicles in cardiomyoblasts using structured illumination microscopy
I. S. Opstad, G.Godtliebsen, B.S. Ahluwalia, T. Myrmel, K. Agarwal, and Å. B. Birgisdottir
Journal of Biophotonics (2022)
Physics-guided loss functions improve deep learning performance in inverse scattering
L. Zicheng, M. Roy, D. K. Prasad, and K. Agarwal
IEEE Transactions on Computational Imaging (2022)
Virtual labeling of mitochondria in living cells using correlative imaging and physics-guided deep learning
A. Somani, A. A. Sekh, I. S. Opstad, Å. B. Birgisdottir, T. Myrmel, B.S. Ahluwalia, A. Horsch, K. Agarwal, and D. K. Prasad
Biomedical Optics Express (2022)
Scalable-resolution structured illumination microscopy
A. Butola, S. Acuna, D. H. Hansen, K. Agarwal
Optics Express (2022)
Image Inpainting With Hypergraphs for Resolution Improvement in Scanning Acoustic Microscopy
A. Somani, P. Banerjee, M. Rastogi, K. Agarwal, D. K. Prasad, and A. Habib
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, (2023)
MiShape: 3D Shape Modelling of Mitochondria in Microscopy
A. R. Punnakkal, S. S Jadhav, A. Horsch, K. Agarwal, D. K. Prasad
arXiv (2023)
Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
A. R. Punnakkal, G. Godtliebsen, A. Somani, S. A. A. Maldonado, Å. B. Birgisdottir, D. K. Prasad, A. Horsch, and K. Agarwal
JoVE (Journal of Visualized Experiments) (2023)
Image inpainting in acoustic microscopy
P. Banerjee, S. Mishra, N. Yadav, K. Agarwal, F. Melandsø, D. K. Prasad, and A. Habib
AIP Advances (2023)
3D full-wave multi-scattering forward solver for coherent microscopes
Y. Qin, A. Butola, and K. Agarwal
Optics Express (2023). (PDF)
Single-shot multispectral quantitative phase imaging using deep neural network
S. Bhatt, A. Butola, A. Kumar, P. Thapa, A. Joshi, S. Jadhav, N. Singh, D. K. Prasad, K. Agarwal, D. S. Mehta
Applied Optics (2023)
Taxonomy of hybridly polarized Stokes vortex beams
G. Arora, A. Butola, R. Rajput, R. Agarwal, K. Agarwal, A. Horsch, D. K. Prasad, P. Senthilkumaran
arXiv (2023)
High-resolution visualization and assessment of basal and OXPHOS-induced mitophagy in H9c2 cardiomyoblasts
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
Autophagy (2023)
3D refractive index reconstruction from phaseless coherent optical microscopy data using multiple scattering-based inverse solvers – a study
Yingying Qin, Ankit Butola and Krishna Agarwal
Inverse Problems (2023)