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Whole-cell organelle segmentation in volume electron microscopy
Cells contain hundreds of organelles and macromolecular assemblies. Obtaining a
complete understanding of their intricate organization requires the nanometre-level, three …
complete understanding of their intricate organization requires the nanometre-level, three …
A workflow for the automatic segmentation of organelles in electron microscopy image stacks
Electron microscopy (EM) facilitates analysis of the form, distribution, and functional status of
key organelle systems in various pathological processes, including those associated with …
key organelle systems in various pathological processes, including those associated with …
Progress towards mammalian whole-brain cellular connectomics
Neurons are the fundamental structural units of the nervous system—ie, the Neuron Doctrine—
as the pioneering work of Santiago Ramón y Cajal in the 1880's clearly demonstrated …
as the pioneering work of Santiago Ramón y Cajal in the 1880's clearly demonstrated …
Automatic whole cell organelle segmentation in volumetric electron microscopy
Cells contain hundreds of different organelle and macromolecular assemblies intricately
organized relative to each other to meet any cellular demands. Obtaining a complete …
organized relative to each other to meet any cellular demands. Obtaining a complete …
Citizen science, cells and CNNs–deep learning for automatic segmentation of the nuclear envelope in electron microscopy data, trained with volunteer segmentations
Advancements in volume electron microscopy mean it is now possible to generate
thousands of serial images at nanometre resolution overnight, yet the gold standard …
thousands of serial images at nanometre resolution overnight, yet the gold standard …
CebraEM: a practical workflow to segment cellular organelles in volume SEM datasets using a transferable CNN-based membrane prediction
Segmentation of large-volume datasets obtained by volume SEM techniques is a
challenging task that generally requires a considerable amount of human effort. Despite …
challenging task that generally requires a considerable amount of human effort. Despite …
An effective encoder-decoder network for neural cell bodies and cell nucleus segmentation of EM images
Neural systems are complicated networks connected by a large number of neurons through
gap junctions and synapse. At present, for electron microscopy connectomics research …
gap junctions and synapse. At present, for electron microscopy connectomics research …
Modified UNet architecture with less number of learnable parameters for nuclei segmentation
The analysis of cell nuclei plays a vital role in the field of pathology. The process of
identifying the cell nuclei is considered difficult due to several challenges. In this work, we …
identifying the cell nuclei is considered difficult due to several challenges. In this work, we …
Efficient nucleus detection in digital pathology images using multi-task and multi-scale instance segmentation network
M Sun, H Dang, GH Zhang, Z Yao… - 2019 International …, 2019 - ieeexplore.ieee.org
Automatic cell spotting is a challenging problem in biomedical image analysis. Efficient
detection of the nuclei in these cells is important for both clinicians and researchers …
detection of the nuclei in these cells is important for both clinicians and researchers …
Automated segmentation of immunostained cell nuclei in 3D ultramicroscopy images
Detection, segmentation, and quantification of individual cell nuclei is a standard task in
biomedical applications. Due to the increasing volume of acquired image data, it is not …
biomedical applications. Due to the increasing volume of acquired image data, it is not …