5 citations · 8 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…