Recent advances in computer vision and machine learning underpin a collection of
algorithms with an impressive ability to decipher the content of images. These deep learning …

Abstract Multiple Object Tracking (MOT) has gained increasing attention due to its academic
and commercial potential. Although different approaches have been proposed to tackle this …

The majority of existing solutions to the Multi-Target Tracking (MTT) problem do not combine
cues over a long period of time in a coherent fashion. In this paper, we present an online …

Achieving complete understanding of any living thing inevitably requires thorough analysis
of both its anatomic and dynamic properties. Live-cell imaging experiments carried out to …

Motivation: Automatic tracking of cells in multidimensional time-lapse fluorescence
microscopy is an important task in many biomedical applications. A novel framework for …

Ever since the establishment of cell theory in the early 19th century, which recognized the
cell as the fundamental building unit of life, biologists have sought to explain the underlying …

Particle tracking is of key importance for quantitative analysis of intracellular dynamic
processes from time-lapse microscopy image data. Because manually detecting and …

Flow cytometry allows highly quantitative analysis of complex dissociated populations at the
cost of neglecting their tissue localization. In contrast, conventional microscopy methods …

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 …

Deep learning of artificial neural networks has become the de facto standard approach to
solving data analysis problems in virtually all fields of science and engineering. Also in …