Article

CebraEM: A practical workflow to segment cellular organelles in volume SEM datasets using a transferable CNN-based membrane prediction

2023-04-06

Abstract excerpt

Segmentation of large-volume datasets obtained by volume SEM techniques is a challenging task that generally requires a considerable amount of human effort. Despite recent advances in deep learning leading to the successful segmentation of cellular organelles in a variety of datasets, it is still challenging and time-consuming to produce the necessary data for training a convolutional neural network as well as to...

Topics

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

Identifiers and source

Literature Corpus work: d191ac71-ff86-5c8c-bf85-4d81293fd93e
DOI: 10.1101/2023.04.06.535829

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

CebraEM: A practical workflow to segment cellular organelles in volume SEM datasets using a transferable CNN-based membrane predictionDOI 10.1101/2023.04.06.535829Read

A general method for bootstrapping dense 3D segmentations from sparse 2D annotationsSemantic proximity Read

Unsupervised Multi-scale Segmentation of Cellular cryo-electron Tomograms with Stable Diffusion Foundation ModelSemantic proximity Read

Unifying the Electron Microscopy Multiverse through a Large-scale Foundation ModelSemantic proximity Read

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

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

Robust Segmentation of Cellular Ultrastructure on Sparsely Labeled 3D Electron Microscopy Images using Deep LearningSemantic proximity Read

CryoViT: Efficient Segmentation of Cryogenic Electron Tomograms with Vision Foundation ModelsSemantic proximity Read

Unifying the Electron Microscopy Multiverse through a Large-scale Foundation ModelSemantic proximity Read

NanTex enables computational multiplexing and phenotyping of organelles across super-resolution modalitiesSemantic proximity Read

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

SynSeg: A synthetic data-driven approach for robust subcellular structure segmentation.Semantic proximity Read

The Allen Cell and Structure Segmenter: a new open source toolkit for segmenting 3D intracellular structures in fluorescence microscopy imagesSemantic proximity Read