Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …

Abstract The Cell Tracking Challenge is an ongoing benchmarking initiative that has
become a reference in cell segmentation and tracking algorithm development. Here, we …

Automated microscopy has given researchers access to great amounts of live cell imaging
data from in vitro and in vivo experiments. Much focus has been put on extracting cell tracks …

The proliferative activity of breast tumors, which is routinely estimated by counting of mitotic
figures in hematoxylin and eosin stained histology sections, is considered to be one of the …

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

Background Algorithmic cellular segmentation is an essential step for the quantitative
analysis of highly multiplexed tissue images. Current segmentation pipelines often require …

The accurate segmentation and tracking of cells in microscopy image sequences is an
important task in biomedical research, eg, for studying the development of tissues, organs or …

Supplying a comprehensive overview of healthcare analytics research, Healthcare Data
Analytics provides an understanding of the analytical techniques currently available to solve …

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 …