5 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…
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…
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…
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…
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…