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...
Image processing is one of the most important applications of recent machine learning (ML) technologies. Convolutional neural networks (CNNs), a popular deep learning-based ML architecture, have been developed for image processing applications. Howev...
Segmentation of three-dimensional (3D) electron microscopy (EM) image stacks is an arduous and tedious task. Deep convolutional neural networks (CNNs) work well to automate the segmentation; however, they require a large training dataset, which is a ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Neural systems are complicated networks connected by a large number of neurons through gap junctions and synapse. At present, for electron microscopy connectomics research, neuron structure recognition algorithms mostly focus on synapses, dendrites, ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Recent studies have shown that the synaptic plasticity induced by development and learning can promote the formation of multiple synapse. With the rapid development of electron microscopy (EM) technology, we can closely observe the multiple synapse s...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
Segmentation is one of the most ubiquitous problems in biological image analysis. Here we present a machine learning-based solution to it as implemented in the open source ilastik toolkit. We give a broad description of the underlying theory and demo...
In this paper, we present a novel error measure to compare a computer-generated segmentation of images or volumes against ground truth. This measure, which we call Tolerant Edit Distance (TED), is motivated by two observations that we usually encount...
MOTIVATION: Accurate segmentation of brain electron microscopy (EM) images is a critical step in dense circuit reconstruction. Although deep neural networks (DNNs) have been widely used in a number of applications in computer vision, most of these mo...
The aim is to study the effects and underlying mechanisms of astragalus polysaccharide (APS) on the peroxide-induced injury in C2C12 myoblasts in vitro. Cell viability in the presence or absence of APS was detected by the methyl thiazolyl tetrazolium...