Article

NuSeT: A Deep Learning Tool for Reliably Separating and Analyzing Crowded Cells

2019-08-28

Abstract excerpt

Segmenting cell nuclei within microscopy images is a ubiquitous task in biological research and clinical applications. Unfortunately, segmenting low-contrast overlapping objects that may be tightly packed is a major bottleneck in standard deep learning-based models. We report a Nu clear Se gmentation T ool (NuSeT) based on deep learning that accurately segments nuclei across multiple types of fluorescence imagi...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 36a0c34b-9f29-5a68-b0dc-e42c9e60ac2d
DOI: 10.1101/749754

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

NuSeT: A Deep Learning Tool for Reliably Separating and Analyzing Crowded CellsDOI 10.1101/749754Read

UNSEG: unsupervised segmentation of cells and their nuclei in complex tissue samplesSemantic proximity Read

CellBinDB: A Large-Scale Multimodal Annotated Dataset for Cell Segmentation with Benchmarking of Universal ModelsSemantic proximity Read

CellSAM: A Foundation Model for Cell SegmentationSemantic proximity Read

Penumbria: Advanced 3D cell segmentation for biomedical imagingSemantic proximity Read

Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learningSemantic proximity Read

Ensemble Processing and Synthetic Image Generation for Abnormally Shaped Nuclei SegmentationSemantic proximity Read

CellSeg3D: self-supervised 3D cell segmentation for fluorescence microscopySemantic proximity Read

UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissuesSemantic proximity Read

Precise cell recovery by cell nucleus united transcript (CellCUT) for enhanced spatial transcriptomicsSemantic proximity Read

SynSeg: Generating Synthetic Datasets for Accurate Subcellular Segmentation with U-netSemantic proximity Read

Fusion of encoder-decoder deep networks improves delineation of multiple nuclear phenotypes.Semantic proximity Read

Evaluation of cell segmentation methods without reference segmentationsSemantic proximity Read