AIMC Topic: Mitochondria

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Analyzing Mitochondrial Morphology Through Simulation Supervised Learning.

Journal of visualized experiments : JoVE Mar 3, 2023
The quantitative analysis of subcellular organelles such as mitochondria in cell fluorescence microscopy images is a demanding task because of the inherent challenges in the segmentation of these small and morphologically diverse structures. In this ...
Microscopy, Fluorescence Supervised Machine Learning Mitochondria Machine Learning Image Processing, Computer-Assisted
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Deep neural network automated segmentation of cellular structures in volume electron microscopy.

The Journal of cell biology Dec 5, 2022
Volume electron microscopy is an important imaging modality in contemporary cell biology. Identification of intracellular structures is a laborious process limiting the effective use of this potentially powerful tool. We resolved this bottleneck with...
Golgi Apparatus Caveolae Endoplasmic Reticulum Microscopy, Electron Clathrin Cell Biology Nuclear Pore Neural Networks, Computer Image Processing, Computer-Assisted Mitochondria
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DeepContact: High-throughput quantification of membrane contact sites based on electron microscopy imaging.

The Journal of cell biology Aug 5, 2022
Membrane contact site (MCS)-mediated organelle interactions play essential roles in the cell. Quantitative analysis of MCSs reveals vital clues for cellular responses under various physiological and pathological conditions. However, an efficient tool...
Microscopy, Electron Endoplasmic Reticulum Mitochondrial Membranes Deep Learning Cells, Cultured Mitochondria Cell Membrane
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Deep learning based domain adaptation for mitochondria segmentation on EM volumes.

Computer methods and programs in biomedicine Jun 14, 2022
BACKGROUND AND OBJECTIVE: Accurate segmentation of electron microscopy (EM) volumes of the brain is essential to characterize neuronal structures at a cell or organelle level. While supervised deep learning methods have led to major breakthroughs in ...
Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Mitochondria Microscopy, Electron
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Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning.

Nature cell biology Dec 7, 2021
Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales is a long-standing goal in biology and medicine, for which progress is hindered by limits of conventional imaging modalities. Here we propose us...
Electron Microscope Tomography COS Cells Lipid Droplets Actins Cell Membrane Optical Imaging Refractometry Cell Nucleolus Subcellular Fractions 3T3 Cells HEK293 Cells Cell Nucleus Chlorocebus aethiops HeLa Cells Deep Learning Cell Line, Tumor Humans Single-Cell Analysis Imaging, Three-Dimensional Animals Mice Mitochondria
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Stable Deep Neural Network Architectures for Mitochondria Segmentation on Electron Microscopy Volumes.

Neuroinformatics Dec 2, 2021
Electron microscopy (EM) allows the identification of intracellular organelles such as mitochondria, providing insights for clinical and scientific studies. In recent years, a number of novel deep learning architectures have been published reporting ...
Humans Neural Networks, Computer Reproducibility of Results Image Processing, Computer-Assisted Mitochondria Microscopy, Electron
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Aligned Organization of Synapses and Mitochondria in Auditory Hair Cells.

Neuroscience bulletin Nov 27, 2021
Recent studies have revealed great functional and structural heterogeneity in the ribbon-type synapses at the basolateral pole of the isopotential inner hair cell (IHC). This feature is believed to be critical for audition over a wide dynamic range, ...
Animals Mice Mitochondria Synapses Cochlea Hair Cells, Auditory, Inner Artificial Intelligence
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Isolation and reconstruction of cardiac mitochondria from SBEM images using a deep learning-based method.

Journal of structural biology Nov 3, 2021
Mitochondrial morphological defects are a common feature of diseased cardiac myocytes. However, quantitative assessment of mitochondrial morphology is limited by the time-consuming manual segmentation of electron micrograph (EM) images. To advance un...
Myocytes, Cardiac Deep Learning Image Processing, Computer-Assisted Mitochondria
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Machine learning-based classification of mitochondrial morphology in primary neurons and brain.

Scientific reports Mar 4, 2021
The mitochondrial network continually undergoes events of fission and fusion. Under physiologic conditions, the network is in equilibrium and is characterized by the presence of both elongated and punctate mitochondria. However, this balanced, homeos...
Humans Nerve Net Image Processing, Computer-Assisted Mitochondrial Dynamics Neurons Mice Machine Learning Microscopy, Electron, Scanning Brain Mitochondria Animals
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DeepACSON automated segmentation of white matter in 3D electron microscopy.

Communications biology Feb 10, 2021
Tracing the entirety of ultrastructures in large three-dimensional electron microscopy (3D-EM) images of the brain tissue requires automated segmentation techniques. Current segmentation techniques use deep convolutional neural networks (DCNNs) and r...
White Matter Rats Animals Nerve Fibers, Myelinated Image Interpretation, Computer-Assisted Brain Injuries, Traumatic Male Artificial Intelligence Disease Models, Animal Cell Nucleus Rats, Sprague-Dawley Imaging, Three-Dimensional Predictive Value of Tests Microscopy, Electron Reproducibility of Results Mitochondria
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