Electron microscopy (EM) enables high-resolution imaging of tissues and cells based on 2D
and 3D imaging techniques. Due to the laborious and time-consuming nature of manual …

Tissue morphogenesis results from a tight interplay between gene expression, biochemical
signaling and mechanics. Although sequencing methods allow the generation of cell …

Unsupervised video object segmentation aims to segment a target object in the video
without a ground truth mask in the initial frame. This challenging task requires extracting …

Topological deep learning is a rapidly growing field that pertains to the development of deep
learning models for data supported on topological domains such as simplicial complexes …

In this work, we describe a method for large-scale 3D cell-tracking through a segmentation
selection approach. The proposed method is effective at tracking cells across large …

Superpixel aggregation is a powerful tool for automated neuron segmentation from electron
microscopy (EM) volume. However, existing graph partitioning methods for superpixel …

We present a new set of computational tools that enable accurate and widely applicable 3D
segmentation of nuclei in various 3D digital organs. We have developed an approach for …

Decades of research have not yet fully explained the mechanisms of epithelial self-
organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for …

We address the problem of detecting tree rings in microscopy images of shrub cross
sections. This can be regarded as a special case of the instance segmentation task with …

Connectomics deals with the problem of reconstructing neural circuitry from electron
microscopy images at the synaptic level. Automatically reconstructing circuits from these …