17 citations · 36 across the 15 of their papers we have counts for
16 papers
Motion-guided sparse correction enables expert-quality point tracking across diverse microscopy regimes
Leonidas Zimianitis, Pasindu Thenahandi, Kai Buckhalter +10
Tracking the dynamics of non-canonical biological systems in microscopy videos remains a persistent challenge. Both classical and learning-based trackers depend on expert-reviewed…
Beyond Perfect Scores: Proof-by-Contradiction for Trustworthy Machine Learning
Dushan N. Wadduwage, Dineth Jayakody, Leonidas Zimianitis
Machine learning (ML) models show strong promise for new biomedical prediction tasks, but concerns about trustworthiness have hindered their clinical adoption. In particular, it is…
Uncertainty Awareness Enables Efficient Labeling for Cancer Subtyping in Digital Pathology
Nirhoshan Sivaroopan, Chamuditha Jayanga Galappaththige, Chalani Ekanayake +4
Machine-learning-assisted cancer subtyping is a promising avenue in digital pathology. Cancer subtyping models, however, require careful training using expert annotations so that t…
Thinking in Groups: Permutation Tests Reveal Near-Out-of-Distribution
Yasith Jayawardana, Dineth Jayakody, Sampath Jayarathna +1
Deep neural networks (DNNs) have the potential to power many biomedical workflows, but training them on truly representative, IID datasets is often infeasible. Most models instead…
QuATON: Quantization Aware Training of Optical Neurons
Hasindu Kariyawasam, Ramith Hettiarachchi, Quansan Yang +7
Optical processors, built with "optical neurons", can efficiently perform high-dimensional linear operations at the speed of light. Thus they are a promising avenue to accelerate l…
Contrastive Deep Encoding Enables Uncertainty-aware Machine-learning-assisted Histopathology
Nirhoshan Sivaroopan, Chamuditha Jayanga, Chalani Ekanayake +6
Deep neural network models can learn clinically relevant features from millions of histopathology images. However generating high-quality annotations to train such models for each…
MOSAIC: Masked Optimisation with Selective Attention for Image Reconstruction
Pamuditha Somarathne, Tharindu Wickremasinghe, Amashi Niwarthana +3
Compressive sensing (CS) reconstructs images from sub-Nyquist measurements by solving a sparsity-regularized inverse problem. Traditional CS solvers use iterative optimizers with h…
DEEP: Deep Learning Powered De-scattering with Excitation Patterning
Navodini Wijethilake, Mithunjha Anandakumar, Cheng Zheng +3
Limited throughput is a key challenge in in-vivo deep-tissue imaging using nonlinear optical microscopy. Point scanning multiphoton microscopy, the current gold standard, is slow e…
Deep Optical Coding Design in Computational Imaging
Henry Arguello, Jorge Bacca, Hasindu Kariyawasam +10
Computational optical imaging (COI) systems leverage optical coding elements (CE) in their setups to encode a high-dimensional scene in a single or multiple snapshots and decode it…
From Hours to Seconds: Towards 100x Faster Quantitative Phase Imaging via Differentiable Microscopy
Udith Haputhanthri, Kithmini Herath, Ramith Hettiarachchi +5
With applications ranging from metabolomics to histopathology, quantitative phase microscopy (QPM) is a powerful label-free imaging modality. Despite significant advances in fast m…
Differentiable Microscopy for Content and Task Aware Compressive Fluorescence Imaging
Udith Haputhanthri, Andrew Seeber, Dushan Wadduwage
The trade-off between throughput and image quality is an inherent challenge in microscopy. To improve throughput, compressive imaging under-samples image signals; the images are th…
Differentiable Microscopy Designs an All Optical Phase Retrieval Microscope
Kithmini Herath, Hasindu Kariyawasam, Ramith Hettiarachchi +7
Designing new optical systems from the ground up for microscopy imaging tasks such as phase retrieval, requires substantial scientific expertise and creativity. To augment the trad…
3D Deep Learning Enables Fast Imaging of Spines through Scattering Media by Temporal Focusing Microscopy
Zhun Wei, Josiah R. Boivin, Yi Xue +4
Today the gold standard for in vivo imaging through scattering tissue is the point-scanning two-photon microscope (PSTPM). Especially in neuroscience, PSTPM is widely used for deep…
Multiline Orthogonal Scanning Temporal Focusing (mosTF) Microscopy for Scattering Reduction in High-speed in vivo Brain Imaging
Yi Xue, Josiah R. Boivin, Dushan N. Wadduwage +3
Temporal focusing two-photon microscopy enables high resolution imaging of fine structures in vivo over a large volume. A limitation of temporal focusing is that signal-to-backgrou…
De-scattering with Excitation Patterning (DEEP) Enables Rapid Wide-field Imaging Through Scattering Media
Dushan N. Wadduwage, Jong Kang Park, Josiah R. Boivin +2
From multi-photon imaging penetrating millimeters deep through scattering biological tissue, to super-resolution imaging conquering the diffraction limit, optical imaging technique…
Chip-based Resonance Raman Spectroscopy Using Tantalum Pentoxide Waveguides
David A. Coucheron, Dushan N. Wadduwage, G. Senthil Murugan +2
Blood analysis is an important diagnostic tool, as it provides a wealth of information about the patient health. Raman spectroscopy is a promising tool in blood analysis, but wides…