Marcelo Cicconet

The paper introduces two methods to improve tissue segmentation in highly multiplexed images using real augmentations and nuclear envelope imaging, resulting in more accurate models.

PuBliCiTy provides a Python toolkit for biological image analysis, including tools for large image processing, web annotation, and machine learning model development.

The paper introduces a GUI toolkit for registering brain slices and assigning them to planes from the Allen Mouse Brain Atlas, using symmetry constraints and dynamic programming.

This study maps the molecular and spatial organization of cell subtypes in the mouse dorsal raphe nucleus using single-cell RNA sequencing and spatial profiling.

The paper introduces software bots for analyzing image-based transcriptomic data, offering algorithms for nuclei segmentation and spot detection, with a machine learning model for challenging segmentation tasks.

The paper presents whole-brain serial-section electron microscopy data of a larval zebrafish, enabling reconstruction of neuronal processes and analysis of axonal symmetry and connectivity.