Réka Hollandi

A Morpho-Proteomic Atlas of Mitosis at Sub-Minute Resolution

This study creates a high-resolution morpho-proteomic atlas of mitosis by decomposing it into 40 subsections and quantifying 4,350 proteins, revealing dynamic changes and links to cancer mutations.

When the pen is mightier than the sword: semi-automatic 2 and 3D image labelling

The paper introduces a semi-automatic annotation tool for 2D and 3D image labelling to reduce expert effort in creating object-based labels.

AI-driven Deep Visual Proteomics defines cell identity and heterogeneity

Pairing AI-driven image analysis with automated laser microdissection and sensitive mass spectrometry yields proteomes of single cells or nuclei chosen by their morphology, with tissue position retained.

OpSeF: Open source Python framework for collaborative instance segmentation of bioimages

OpSeF provides a Python framework for collaborative instance segmentation of bioimages, integrating pre-trained models and enabling reproducible, modular workflows.

AnnotatorJ: an ImageJ plugin to ease hand-annotation of cellular compartments

AnnotatorJ is an ImageJ plugin that combines deep learning and manual annotation to improve cell segmentation and annotation efficiency.

A deep learning framework for nucleus segmentation using image style transfer

The paper introduces a deep learning framework for nucleus segmentation that uses image style transfer to adapt to new data without expert annotations, outperforming existing methods on diverse microscopy images.

Test-time augmentation for deep learning-based cell segmentation on microscopy images

This paper applies test-time augmentation to improve cell segmentation accuracy in microscopy images using U-Net and Mask R-CNN models, achieving a better score in the DSB 2018 competition.