Electron Microscopy Image Segmentation

8 papers with code • 3 benchmarks • 1 datasets

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Most implemented papers

Superhuman Accuracy on the SNEMI3D Connectomics Challenge

wolny/pytorch-3dunet 31 May 2017

For the past decade, convolutional networks have been used for 3D reconstruction of neurons from electron microscopic (EM) brain images.

MEDIAR: Harmony of Data-Centric and Model-Centric for Multi-Modality Microscopy

lee-gihun/mediar 7 Dec 2022

Cell segmentation is a fundamental task for computational biology analysis.

Large-Scale Electron Microscopy Image Segmentation in Spark

janelia-flyem/DVIDSparkServices 1 Apr 2016

In this paper, we propose a novel strategy to apply such segmentation on very large datasets that exceed the capacity of a single machine.

SSHMT: Semi-supervised Hierarchical Merge Tree for Electron Microscopy Image Segmentation

tingliu/glia 14 Aug 2016

We then propose a Bayesian model that combines the supervised and the unsupervised information for probabilistic learning.

UNI-EM: An Environment for Deep Neural Network-Based Automated Segmentation of Neuronal Electron Microscopic Images

urakubo/UNI-EM bioRxiv Neuroscience 2019

The spatial scale of the 3D reconstruction grows rapidly owing to deep neural networks (DNNs) that enable automated image segmentation.

TeraVR empowers precise reconstruction of complete 3-D neuronal morphology in the whole brain

Vaa3D/release Nature Communicationsvolume 10, Article number: 3474 (2019) 2019

Neuron morphology is recognized as a key determinant of cell type, yet the quantitative profiling of a mammalian neuron’s complete three-dimensional (3-D) morphology remains arduous when the neuron has complex arborization and long projection.

CEM500K – A large-scale heterogeneous unlabeled cellular electron microscopy image dataset for deep learning

volume-em/cellemnet 11 Dec 2020

Automated segmentation of cellular electron microscopy (EM) datasets remains a challenge.

Dense cellular segmentation for EM using 2D–3D neural network ensembles

leapmanlab/examples 28 Jan 2021

Here, we define dense cellular segmentation as a multiclass semantic segmentation task for modeling cells and large numbers of their organelles, and give an example in human blood platelets.