Articles with "cell segmentation" as a keyword



Cell Segmentation for Image Cytometry: Advances, Insufficiencies, and Challenges

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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

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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

Deep Learning-Based Quality Control Using Subcellular RNA Spatial Distribution Patterns for Cell Segmentation in Spatial Transcriptomics Data.

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Published in 2025 at "Small methods"

DOI: 10.1002/smtd.202500885

Abstract: Sequencing‐based spatial transcriptomics (sST) techniques with high resolution enable transcriptome‐wide RNA capture at subcellular resolution. Although new cell segmentation methods for sST data are continually being developed, accurately assigning RNA spots to corresponding cells still… read more here.

Keywords: quality; quality control; segmentation; rna ... See more keywords

A Cell Segmentation/Tracking Tool Based on Machine Learning.

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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

From spots to cells: Cell segmentation in spatial transcriptomics with BOMS

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Published in 2024 at "PLOS One"

DOI: 10.1101/2024.09.21.614281

Abstract: Imaging-based Spatial Transcriptomics methods enable the study of gene expression and regulation in complex tissues at subcellular resolution. However, inaccurate cell segmentation procedures lead to misassignment of mRNAs to individual cells which can introduce errors… read more here.

Keywords: spatial transcriptomics; segmentation spatial; cells cell; spots cells ... See more keywords

MTCSNet: One-Stage Learning and Two-Point Labeling are Sufficient for Cell Segmentation

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Published in 2024 at "IEEE Transactions on Medical Imaging"

DOI: 10.1109/tmi.2024.3404428

Abstract: Deep convolution neural networks have been widely used in medical image analysis, such as lesion identification in whole-slide images, cancer detection, and cell segmentation, etc. However, it is often inevitable that researchers try their best… read more here.

Keywords: segmentation; mtcsnet; stage learning; 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.

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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

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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

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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

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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

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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