AIMC Topic: Microscopy, Electron

Clear Filters Showing 51 to 60 of 66 articles

Automated tracing of myelinated axons and detection of the nodes of Ranvier in serial images of peripheral nerves.

Journal of microscopy
The development of realistic neuroanatomical models of peripheral nerves for simulation purposes requires the reconstruction of the morphology of the myelinated fibres in the nerve, including their nodes of Ranvier. Currently, this information has to...

Learning structured models for segmentation of 2-D and 3-D imagery.

IEEE transactions on medical imaging
Efficient and accurate segmentation of cellular structures in microscopic data is an essential task in medical imaging. Many state-of-the-art approaches to image segmentation use structured models whose parameters must be carefully chosen for optimal...

3BTRON: A Blood-Brain Barrier Recognition Network.

Communications biology
The blood-brain barrier (BBB) plays a crucial role in maintaining brain homeostasis. During ageing, the BBB undergoes structural alterations. Electron microscopy (EM) is the gold standard for studying the structural alterations of the brain vasculatu...

A guide to CNN-based dense segmentation of neuronal EM images.

Microscopy (Oxford, England)
Large-scale reconstitution of neuronal circuits from volumetric electron microscopy images is a remarkable research goal in neuroanatomy. However, the large-scale reconstruction is a result of automatic segmentation using convolutional neural network...

Recent advancement and human tissue applications of volume electron microscopy.

Microscopy (Oxford, England)
Structural observations are essential for the advancement of life science. Volume electron microscopy has recently realized remarkable progress in the three-dimensional analyses of biological specimens for elucidating complex ultrastructures in sever...

Automated cell structure extraction for 3D electron microscopy by deep learning.

Scientific reports
Modeling the 3D structures of cells and tissues is crucial in biology. Sequential cross-sectional images from electron microscopy provide high-resolution intracellular structure information. The segmentation of complex cell structures remains a labor...

Mesoscopic structural analysis via deep learning processing, with a special reference to in vitro alteration in collagen fibre induced by a gap junction inhibitor.

Microscopy (Oxford, England)
Dense connective tissue, including the ligament, tendon, fascia and cornea, is formed by regularly arranged collagen fibres synthesized by fibroblasts (Fbs). The mechanism by which fibre orientation is determined remains unclear. Periodontal ligament...

Instance segmentation of mitochondria in electron microscopy images with a generalist deep learning model trained on a diverse dataset.

Cell systems
Mitochondria are extremely pleomorphic organelles. Automatically annotating each one accurately and precisely in any 2D or volume electron microscopy (EM) image is an unsolved computational challenge. Current deep learning-based approaches train mode...

Fear memory-associated synaptic and mitochondrial changes revealed by deep learning-based processing of electron microscopy data.

Cell reports
Serial section electron microscopy (ssEM) can provide comprehensive 3D ultrastructural information of the brain with exceptional computational cost. Targeted reconstruction of subcellular structures from ssEM datasets is less computationally demandin...

Applications of deep learning in electron microscopy.

Microscopy (Oxford, England)
We review the growing use of machine learning in electron microscopy (EM) driven in part by the availability of fast detectors operating at kiloHertz frame rates leading to large data sets that cannot be processed using manually implemented algorithm...