ArticleJournal of structural biology2018
A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation.
Article in Journal of structural biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- PickET: An unsupervised method for localizing macromolecules in cryo-electron tomograms.Research square · 2025Article
- PickET: An unsupervised method for localizing macromolecules in cryo-electron tomograms.bioRxiv : the preprint server for biology · 2025Article
- AITom: AI-guided cryo-electron tomography image analyses toolkit.Journal of structural biology · 2025Article
- High-throughput cryo-ET structural pattern mining by unsupervised deep iterative subtomogram clustering.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- CryomicroscopyFaraday discussions · 2022Article
- Spaghetti Tracer: A Framework for Tracing Semiregular Filamentous Densities in 3D Tomograms.Biomolecules · 2022Article
- Better, Faster, Cheaper: Recent Advances in Cryo-Electron Microscopy.Annual review of biochemistry · 2022Review
- CryoETGAN: Cryo-Electron Tomography Image SynthesisFrontiers in physiology · 2022Article
- Self-supervised learning for macromolecular structure classification based on cryo-electron tomograms.Frontiers in physiology · 2022Article
- Air-Writing Character Recognition with Ultrasonic Transceivers.Sensors (Basel, Switzerland) · 2021Article
- Weakly Supervised 3D Semantic Segmentation Using Cross-Image Consensus and Inter-Voxel Affinity Relations.Proceedings. IEEE International Conference on Computer Vision · 2021Article
- A unified framework for packing deformable and non-deformable subcellular structures in crowded cryo-electron tomogram simulation.BMC bioinformatics · 2020Article
- Looking back and looking forward: contributions of electron microscopy to the structural cell biology of gametes and fertilization.Open biology · 2020Review
- Quality Assessment of the Neural Algorithms on the Example of EIT-UST Hybrid Tomography.Sensors (Basel, Switzerland) · 2020Article
- Investigating eukaryotic cells with cryo-ET.Molecular biology of the cell · 2020Article
- Adversarial domain adaptation for cross data source macromolecule in situ structural classification in cellular electron cryo-tomograms.Bioinformatics (Oxford, England) · 2019Article
- A collection of yeast cellular electron cryotomography data.GigaScience · 2019Article
- Securing the future of research computing in the biosciences.PLoS computational biology · 2019Article
- Automatic localization and identification of mitochondria in cellular electron cryo-tomography using faster-RCNN.BMC bioinformatics · 2019Article
- Feature Decomposition Based Saliency Detection in Electron Cryo-Tomograms.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2018Article
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4 authors.
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Abstract
Cellular electron cryo-tomography enables the 3D visualization of cellular organization in the near-native state and at submolecular resolution. However, the contents of cellular tomograms are often complex, making it difficult to automatically isolate different in situ cellular components. In this paper, we propose a convolutional autoencoder-based unsupervised approach to provide a coarse grouping of 3D small subvolumes extracted from tomograms. We demonstrate that the autoencoder can be used for efficient and coarse characterization of features of macromolecular complexes and surfaces, such as membranes. In addition, the autoencoder can be used to detect non-cellular features related to sample preparation and data collection, such as carbon edges from the grid and tomogram boundaries. The autoencoder is also able to detect patterns that may indicate spatial interactions between cellular components. Furthermore, we demonstrate that our autoencoder can be used for weakly supervised semantic segmentation of cellular components, requiring a very small amount of manual annotation.
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