Frédéric Beaupré

Astro-BEATS detects and segments miniature synaptic calcium transients in fluorescence imaging using astronomical transient detection techniques, outperforming threshold-based methods and enabling efficient training of deep learning models.

This paper introduces STED-FM, a foundation model for STED microscopy that learns robust representations without extensive annotations, improving downstream tasks like classification, segmentation, and image denoising.

This paper introduces a PU learning-based method for detecting and segmenting miniature synaptic calcium transients, showing improved performance over traditional methods in cultured rat neurons.