Accelerating SMLM Image Analysis with AI

Collaboration with Abbelight

At BionomeeX, we recently partnered with Abbelight, a leader in super-resolution microscopy, to develop a complete AI-powered pipeline for analyzing Single Molecule Localization Microscopy (SMLM) images.

The Challenge

SMLM allows researchers to observe cellular structures at the nanometer scale by localizing individual fluorescent emitters.

However, analyzing SMLM images is challenging due to:

• Image noise

• Overlapping signals

• Large datasets generated during acquisition

Accurately detecting and counting emitters manually is time-consuming and error-prone.

Our AI-Powered Solution

BionomeeX designed an integrated pipeline that streamlines the entire workflow, from data preparation to model training and prediction.

The pipeline specifically enables:

1. Data Preparation – cleaning, normalization, and annotation of microscopy datasets

2. AI Model Training – detecting and quantifying emitters at the pixel level

3. Prediction – automated detection and counting of emitters in new SMLM images

Impact

This AI solution:

• Reduces analysis time significantly compared to manual or semi-automated methods

• Improves accuracy and reproducibility

• Precisely identifies and counts emitters even in complex or noisy conditions

Driving Biological Insights

This collaboration embodies BionomeeX’s mission: leveraging artificial intelligence to transform imaging data into meaningful biological insights, empowering researchers to accelerate discovery in life sciences.