We present ilastik, an easy-to-use interactive tool that brings machine-learning-based (bio)
image analysis to end users without substantial computational expertise. It contains pre …

In this review, we discuss the emerging field of computational behavioral analysis—the use
of modern methods from computer science and engineering to quantitatively measure …

We present a combined report on the results of three editions of the Cell Tracking
Challenge, an ongoing initiative aimed at promoting the development and objective …

Recent developments in machine vision methods for automatic, quantitative analysis of
social behavior have immensely improved both the scale and level of resolution with which …

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 …

Cell tracking is a ubiquitous image analysis task in live-cell microscopy. Unlike multiple
object tracking (MOT) for natural images, cell tracking typically involves hundreds of similar …

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 …

In multi-object tracking, it is critical to explore the data associations by exploiting the
temporal information from a sequence of frames rather than the information from the …

Pathogens face varying microenvironments in vivo, but suitable experimental systems and
analysis tools to dissect how three-dimensional (3D) tissue environments impact pathogen …

Automatic cell segmentation and tracking enables to gain quantitative insights into the
processes driving cell migration. To investigate new data with minimal manual effort, cell …