Collective cell migration, in which cells migrate as a group, is fundamental in many biological and pathological processes. There is increasing interest in studying the collective cell migration in high throughput. Cell scratching, insertion blocker,...
In vitro experiments with cultured cells are essential for studying their growth and migration pattern and thus, for gaining a better understanding of cancer progression and its treatment. Recent progress in lens-free microscopy (LFM) has rendered it...
Methods in molecular biology (Clifton, N.J.)
31432490
The ability to gain quantifiable, single-cell data from time-lapse microscopy images is dependent upon cell segmentation and tracking. Here, we present a detailed protocol for obtaining quality time-lapse movies and introduce a method to identify (se...
Single cell segmentation is a critical and challenging step in cell imaging analysis. Traditional processing methods require time and labor to manually fine-tune parameters and lack parameter transferability between different situations. Recently, de...
We propose a new deep learning approach for medical imaging that copes with the problem of a small training set, the main bottleneck of deep learning, and apply it for classification of healthy and cancer cell lines acquired by quantitative phase ima...
Differently to semantic segmentation, instance segmentation assigns unique labels to each individual instance of the same object class. In this work, we propose a novel recurrent fully convolutional network architecture for tracking such instance seg...
In this paper, we solve the problem of mitosis event localization and its stage localization in time-lapse phase-contrast microscopy images. Our method contains three steps: first, we formulate a Low-Rank Matrix Recovery (LRMR) model to find salient ...
Convolutional neural networks (ConvNets) have proven to be successful in both the classification and semantic segmentation of cell images. Here we establish a method for cell type classification utilizing images taken with a benchtop microscope direc...
BACKGROUND: Cell tracking experiments, based on time-lapse microscopy, have become an important tool in biomedical research. The goal is the reconstruction of cell migration patterns, shape and state changes, and, comprehensive genealogical informati...
IEEE/ACM transactions on computational biology and bioinformatics
31443049
The tracking of densely packed plant cells across microscopy image sequences is very challenging, because their appearance change greatly over time. A local graph matching algorithm was proposed to track such cells by exploiting the tight spatial top...