Anthony Bilodeau

Calcium transient detection and segmentation with the astronomically motivated algorithm for background estimation and transient segmentation (Astro-BEATS)

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.

Enhancing STED Microscopy via Fluorescence Lifetime Unmixing and Filtering in Two-Species SPLIT-STED

This paper introduces a method to improve STED microscopy by using fluorescence lifetime unmixing and filtering to enhance resolution and accuracy in two-species imaging.

A Self-Supervised Foundation Model for Robust and Generalizable Representation Learning in STED Microscopy

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.

Quantitative Analysis of Miniature Synaptic Calcium Transients Using Positive Unlabeled Deep Learning

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.

Development of AI-assisted microscopy frameworks through realistic simulation in pySTED

This paper develops a simulation platform, pySTED, to aid in creating AI-assisted super-resolution microscopy techniques by generating realistic data for training and testing AI models.

Resolution Enhancement with a Task-Assisted GAN to Guide Optical Nanoscopy Image Analysis and Acquisition

This paper introduces TA-GAN, a deep learning model that enhances image resolution in optical nanoscopy by incorporating auxiliary tasks, improving accuracy and enabling online imaging assistance.

MICRA-Net: MICRoscopy Analysis Neural Network to solve detection, classification, and segmentation from a single simple auxiliary task

MICRA-Net is a weakly-supervised neural network that uses a simple classification task to perform segmentation, detection, and enumeration on microscopy images with limited annotated data.

Neuronal activity remodels the F-actin based submembrane lattice in dendrites but not axons of hippocampal neurons

The paper uses deep learning to analyze F-actin structures in hippocampal neurons, showing activity-dependent remodeling in dendrites but not axons.