From the 1 of 5 linked papers with an AI index.
5 papers
Noise-Robust Conditional Flow Matching: Generating Clean Samples from Noisy Datasets
Adrian UrbaÅski, Adrian Urbański, Gabriel della Maggiora +1
Generative models learn the statistical properties of their training data, so high-quality generation depends on clean and representative datasets. In scientific imaging, acquisiti…
Metric-Guided Synthetic Image Data Rendering for Deep Learning compatible with Agentic AI
Martina Radoynova, Samuel Pantze, Trina De +2
The paper introduces GraNatPy, a Python toolkit that uses quantitative metrics to improve the realism and diversity of synthetically rendered images for training deep learning visi…
Cryo-SWAN: the Multi-Scale Wavelet-decomposition-inspired Autoencoder Network for molecular density representation of molecular volumes
Rui Li, Artsemi Yushkevich, Mikhail Kudryashev +1
Learning robust representations of 3D shapes from voxelized data is essential for advancing AI methods in biomedical imaging. However, most contemporary 3D computer vision approach…
Single-shot Star-convex Polygon-based Instance Segmentation for Spatially-correlated Biomedical Objects
Trina De, Adrian Urbanski, Artur Yakimovich
Biomedical images often contain objects known to be spatially correlated or nested due to their inherent properties, leading to semantic relations. Examples include cell nuclei bei…
Single Exposure Quantitative Phase Imaging with a Conventional Microscope using Diffusion Models
Gabriel della Maggiora, Luis Alberto Croquevielle, Harry Horsley +2
Phase imaging is gaining importance due to its applications in fields like biomedical imaging and material characterization. In biomedical applications, it can provide quantitative…