Cell Segmentation for Image Cytometry: Advances, Insufficiencies, and Challenges
Sign Up to like & getrecommendations! Published in 2018 at "Cytometry Part A"
DOI: 10.1002/cyto.a.23686
Abstract: IN the past decades, image cytometry has made great progress due to the advances in optical imaging and image processing. The central problem of image cytometry in many studies is cell segmentation which has received… read more here.
Keywords: image; cell segmentation; image cytometry; image processing ... See more keywords
Sub‐micro scale cell segmentation using deep learning
Sign Up to like & getrecommendations! Published in 2022 at "Cytometry Part A"
DOI: 10.1002/cyto.a.24533
Abstract: Automated cell segmentation is key for rapid and accurate investigation of cell responses. As instrumentation resolving power increases, clear delineation of newly revealed cellular features at the submicron through nanoscale becomes important. Reliance on the… read more here.
Keywords: cell; cell segmentation; microscopy; segmentation ... See more keywords
A Cell Segmentation/Tracking Tool Based on Machine Learning.
Sign Up to like & getrecommendations! Published in 2019 at "Methods in molecular biology"
DOI: 10.1007/978-1-4939-9686-5_19
Abstract: 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… read more here.
Keywords: machine learning; based machine; segmentation; cell segmentation ... See more keywords
Single-cell segmentation in bacterial biofilms with an optimized deep learning method enables tracking of cell lineages and measurements of growth rates.
Sign Up to like & getrecommendations! Published in 2023 at "Molecular microbiology"
DOI: 10.1111/mmi.15064
Abstract: Bacteria often grow into matrix-encased three-dimensional (3D) biofilm communities, which can be imaged at cellular resolution using confocal microscopy. From these 3D images, measurements of single-cell properties with high spatiotemporal resolution are required to investigate… read more here.
Keywords: cell; cell segmentation; segmentation; single cell ... See more keywords
Robust optical flow algorithm for general single cell segmentation
Sign Up to like & getrecommendations! Published in 2022 at "PLoS ONE"
DOI: 10.1371/journal.pone.0261763
Abstract: Cell segmentation is crucial to the field of cell biology, as the accurate extraction of single-cell morphology, migration, and ultimately behavior from time-lapse live cell imagery are of paramount importance to elucidate and understand basic… read more here.
Keywords: cell; cell segmentation; segmentation; single cell ... See more keywords
microbeSEG: A deep learning software tool with OMERO data management for efficient and accurate cell segmentation
Sign Up to like & getrecommendations! Published in 2022 at "PLOS ONE"
DOI: 10.1371/journal.pone.0277601
Abstract: In biotechnology, cell growth is one of the most important properties for the characterization and optimization of microbial cultures. Novel live-cell imaging methods are leading to an ever better understanding of cell cultures and their… read more here.
Keywords: cell; cell segmentation; data management; omero data ... See more keywords
Dice-XMBD: Deep Learning-Based Cell Segmentation for Imaging Mass Cytometry
Sign Up to like & getrecommendations! Published in 2021 at "Frontiers in Genetics"
DOI: 10.3389/fgene.2021.721229
Abstract: Highly multiplexed imaging technology is a powerful tool to facilitate understanding the composition and interactions of cells in tumor microenvironments at subcellular resolution, which is crucial for both basic research and clinical applications. Imaging mass… read more here.
Keywords: dice xmbd; imaging mass; segmentation; cell segmentation ... See more keywords
User-Accessible Machine Learning Approaches for Cell Segmentation and Analysis in Tissue
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Physiology"
DOI: 10.3389/fphys.2022.833333
Abstract: Advanced image analysis with machine and deep learning has improved cell segmentation and classification for novel insights into biological mechanisms. These approaches have been used for the analysis of cells in situ, within tissue, and… read more here.
Keywords: cell segmentation; machine; machine learning; segmentation ... See more keywords
Automated Cell Foreground–Background Segmentation with Phase-Contrast Microscopy Images: An Alternative to Machine Learning Segmentation Methods with Small-Scale Data
Sign Up to like & getrecommendations! Published in 2022 at "Bioengineering"
DOI: 10.3390/bioengineering9020081
Abstract: Cell segmentation is a critical step for image-based experimental analysis. Existing cell segmentation methods are neither entirely automated nor perform well under basic laboratory microscopy. This study proposes an efficient and automated cell segmentation method… read more here.
Keywords: phase contrast; cell segmentation; microscopy; segmentation ... See more keywords