25 papers · ranked by Valyu relevance
Erlend Hodneland, Tanja Kögel, Dominik Michael Frei, Hans-Hermann Gerdes + 1 more
The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to…
Sharif Chowdhury, Meenakshisundaram Kandhavelu, Olli Yli-Harja, Andre S Ribeiro
'Andre S Ribeiro'] Background Cell imaging is becoming an indispensable tool for cell and molecular biology research. However, most processes studied are stochastic in nature, and require the observation of many cells and events. Ideally, extraction of information from these images ought to rely on automatic methods.…
Liang, Peixian, Ding, Yifan + 20 more
— State-of-the-art (SOTA) methods for cell instance segmentation are based on deep learning (DL) semantic segmentation approaches, focusing on distinguishing foreground pixels from background pixels. In order to identify cell instances from foreground pixels (e.g., pixel clustering), most methods decompose instance…
Huixia Ren, Mengdi Zhao, Bo Liu, Ruixiao Yao + 6 more
Time-lapse live cell imaging of a growing cell population is routine in many biological investigations. A major challenge in imaging analysis is accurate segmentation, a process to define the boundaries of cells based on raw image data. Current segmentation methods relying on single boundary features have problems in…
Can Fahrettin Koyuncu, Salim Arslan, Irem Durmaz, Rengul Cetin-Atalay + 2 more
'Rengul Cetin-Atalay' 'Cigdem Gunduz-Demir' 'Konradin Metze'] Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand…
Benjamin Kesler, Guoliang Li, Alexander Thiemicke, Rohit Venkat + 1 more
To characterize cell types, cellular functions and intracellular processes, an understanding of the differences between individual cells is required. Although microscopy approaches have made tremendous progress in imaging cells in different contexts, the analysis of these imaging data sets is a long-standing, unsolved…
Elco Bakker, Peter S. Swain, Matthew M. Crane
Although high-content image cytometry is becoming increasingly routine, processing the large amount of data acquired during time-lapse experiments remains a challenge. The majority of approaches for automated single-cell segmentation focus on flat, uniform fields of view covered with a single layer of cells. In the…
Joe Chalfoun, Michael Majurski, Alden Dima, Christina Stuelten + 2 more
'Adele Peskin' 'Mary Brady'] Background Many cell lines currently used in medical research, such as cancer cells or stem cells, grow in confluent sheets or colonies. The biology of individual cells provide valuable information, thus the separation of touching cells in these microscopy images is critical for counting…
N Ezgi Wood, Andreas Doncic
Live cell time-lapse microscopy, a widely-used technique to study gene expression and protein dynamics in single cells, relies on segmentation and tracking of individual cells for data generation. The potential of the data that can be extracted from this technique is limited by the inability to accurately segment a…
Lena R. Bartell, Lawrence J. Bonassar, Itai Cohen
Imaging assays of cellular function, especially those using fluorescent stains, are ubiquitous in the biological and medical sciences. Despite advances in computer vision, such images are often analyzed using only manual or rudimentary automated processes. Watershed-based segmentation is an effective technique for…
Anubha Gupta, Pramit Mallick, Ojaswa Sharma, Ritu Gupta + 2 more
'Rahul Duggal' 'Yuanquan Wang'] Plasma cell segmentation is the first stage of a computer assisted automated diagnostic tool for multiple myeloma (MM). Owing to large variability in biological cell types, a method for one cell type cannot be applied directly on the other cell types. In this paper, we present PCSeg Tool…
Michael C. Robitaille, Jeff M. Byers, Joseph A. Christodoulides, Marc P. Raphael
Cell segmentation is crucial to the field of cell biology, as the accurate extraction of cell morphology, migration, and ultimately behavior from time-lapse live cell imagery are of paramount importance to elucidate and understand basic cellular processes. Here, we introduce a novel segmentation approach centered…
Leonardo Rundo, Andrea Tangherloni, Darren R. Tyson, Riccardo Betta + 9 more
Advances in microscopy imaging technologies have enabled the visualization of live-cell dynamic processes using time-lapse microscopy imaging. However, modern methods exhibit several limitations related to the training phases and to time constraints, hindering their application in the laboratory practice. In this work…
Nikomidisz Jorgosz Eftimiu, Michal Kozubek
Automatic detection and tracking of cells in microscopy images are major applications of computer vision technologies in both biomedical research and clinical practice. Though machine learning methods are increasingly common in these fields, classical algorithms still offer significant advantages for both tasks…
Felix Schönenberger, Anja Deutzmann, Elisa Ferrando-May, Dorit Merhof
'Dorit Merhof'] Background Protein function in eukaryotic cells is often controlled in a cell cycle-dependent manner. Therefore, the correct assignment of cellular phenotypes to cell cycle phases is a crucial task in cell biology research. Nuclear proteins whose localization varies during the cell cycle are valuable…
Weikang Wang, David A. Taft, Yi‐Jiun Chen, Jingyu Zhang + 4 more
'Callen T. Wallace' 'Min Xu' 'Simon C. Watkins' 'Jianhua Xing'] 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, deep…
Lin Zhang
Phase contrast microscopy (PCM) has been widely used in the biomedicine, which allows users to observe objectives without staining or killing them. One important related research is to employ PCM to monitor live cells. How to segment cell populations in obtained PCM images gains more and more attention as its a…
Anuradha Kar, Manuel Petit, Yassin Refahi, Guillaume Cerutt + 2 more
Segmenting three dimensional microscopy images is essential for understanding phenomena like morphogenesis, cell division, cellular growth and genetic expression patterns. Recently, deep learning (DL) pipelines have been developed which claim to provide high accuracy segmentation of cellular images and are increasingly…
Sholpan Kauanova, Ivan A. Vorobjev, Alex Pappachen James
—The automated segmentation of cells in microscopic images is an open research problem that has important implications for studies of the developmental and cancer processes based on in vitro models. In this paper, we present the approach for segmentation of the DIC images of cultured cells using G-neighbor smoothing…
Peter Bajcsy, Antonio Cardone, Joe Chalfoun, Michael Halter + 8 more
Background The goal of this survey paper is to overview cellular measurements using optical microscopy imaging followed by automated image segmentation. The cellular measurements of primary interest are taken from mammalian cells and their components. They are denoted as two- or three-dimensional (2D or 3D) image…
Authors not listed
Vertex models have been established as powerful tools for the cell-based simulation of epithelial tissues as they allow a detailed description of their mechanical development with respect to the properties of individual cells. Thus, they suit the challenges of simulating intestinal organoids which arise from the…
Kanda Borgognoni, Bradley Guilliams, Rachel Cohen, Christopher Ackerson
A cloneable NanoParticle (cNP) is an inorganic nanoparticle that is synthesized by a protein. The protein determines the elemental composition, size, morphology, and other properties of the nanoparticle. Here, we describe the use of a cloneable Selenium NanoParticle (cSeNP) as a cloneable imaging contrast agent in…
Alexander E. Siemenn, Eunice Aissi, Fang Sheng, Armi Tiihonen + 3 more
In materials research, the task of characterizing hundreds of different materials traditionally requires equally many human hours spent measuring samples one by one. We demonstrate that with the integration of computer vision into this material research workflow, many of these tasks can be automated, significantly…
Authors not listed
Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI-MSI) is a powerful technique for molecular analysis of surfaces; however, its application of single cell studies has not been previously published. In the current work, a commercial DESI setup (DESI XS) coupled to a mass spectrometer was used to analyze…
Authors not listed
The Single-probe is a multifunctional device that can be coupled to mass spectrometry (MS) for molecular analysis of microscale samples, such as single cells, tissue slices, and multicellular spheroids, under ambient conditions. In Single-probe single cell MS (SCMS) studies, this technique leverages direct sampling and…