2 citations · 4 across the 4 of their papers we have counts for
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Convex Potential Learning for Optimal Transport Between Medical Images
Hongyu Kan, Ivan Medri, Natasha Ironside +4
Computing optimal transport maps between medical images plays a fundamental role in morphological analysis. However, existing methods are either difficult to scale to large 3D medi…
Confine to the Task, Anchor the Rest: Concept-Guided Retention Regularizer for Parameter-Efficient Fine-Tuning
Ibna Kowsar, Ivan Medri, Fanyu Meng +1
Parameter-efficient fine-tuning (PEFT) has been widely used, yet the adapted model suffers catastrophic forgetting of pre-trained knowledge. While most existing work hardens the ad…
FlowLOT: Linearized Optimal Transport for Flow Cytometry Analysis
Naqib Sad Pathan, Mohammad Shifat-E-Rabbi, Kristofor E. Pas +3
Multiparameter flow cytometry generates high-dimensional, unordered single-cell mea- surement data for disease diagnosis and monitoring, yet analysis often remains dependent on man…
3D Transport-based Morphometry (3D-TBM) for medical image analysis
Hongyu Kan, Kristofor Pas, Ivan Medri +5
Transport-Based Morphometry (TBM) has emerged as a new framework for 3D medical image analysis. By embedding images into a transport domain via invertible transformations, TBM faci…