In recent years, deep learning has evolved as a rapidly growing and stimulating field of
machine learning and has redefined state-of-the-art performances in a variety of …

To shed light on the processes driving cell migration, a systematic analysis of the cell
behavior is required. Since the manual analysis of hundreds or even thousands of cells is …

We present a novel graph neural network (GNN) approach for cell tracking in high-
throughput microscopy videos. By modeling the entire time-lapse sequence as a direct …

We propose a geometric deep-learning-based framework, TractGeoNet, for performing
regression using diffusion magnetic resonance imaging (dMRI) tractography and associated …

Microscopy cell segmentation is a crucial step in biological image analysis and a
challenging task. In recent years, deep learning has been widely used to tackle this task …

Extracting long tracks and lineages from videomicroscopy requires an extremely low error
rate, which is challenging on complex data sets of dense or deforming cells. Leveraging …

Morphogenesis is a developmental process of organisms being shaped through complex
and cooperative cellular movements. To understand the interplay between genetic programs …

Purpose A PolarMask-based method for blood cell contour segmentation is proposed. The
method is divided into two parts. One part is a weak label-based model pretraining method …

Most bacteria live attached to surfaces in densely-packed communities. While new
experimental and imaging techniques are beginning to provide a window on the complex …

Extracellular vesicles (EVs) are nanoparticles released by cells that contain a multitude of
biomolecules, which act synergistically to signal multiple cell types. EVs are ideal …