The intra-axonal water exchange time (τ), a parameter associated with axonal permeability, could be an important biomarker for understanding and treating demyelinating pathologies such as Multiple Sclerosis. Diffusion-Weighted MRI (DW-MRI) is sensiti...
Biologists who use electron microscopy (EM) images to build nanoscale 3D models of whole cells and their organelles have historically been limited to small numbers of cells and cellular features due to constraints in imaging and analysis. This has be...
Computer methods and programs in biomedicine
33508773
BACKGROUND AND OBJECTIVE: With the advancement of electron microscopy (EM) imaging technology, neuroscientists can investigate the function of various intracellular organelles, e.g, mitochondria, at nano-scale. Semantic segmentation of electron micro...
Computer methods and programs in biomedicine
33588253
BACKGROUND AND OBJECTIVE: Nanoparticles present properties that can be applied to a wide range of fields such as biomedicine, electronics or optics. The type of properties depends on several characteristics, being some of them related with the partic...
Artificial intelligence (AI) is a new frontier and often enigmatic for medical professionals. Cloud computing could open up the field of computer vision to a wider medical audience and deep learning on the cloud allows one to design, develop, train a...
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...
Point-scanning imaging systems are among the most widely used tools for high-resolution cellular and tissue imaging, benefiting from arbitrarily defined pixel sizes. The resolution, speed, sample preservation and signal-to-noise ratio (SNR) of point-...
Electron microscopy (EM) enables high-resolution visualization of protein distributions in biological tissues. For detection, gold nanoparticles are typically used as an electron-dense marker for immunohistochemically labeled proteins. Manual annotat...
Automated segmentation of cellular electron microscopy (EM) datasets remains a challenge. Supervised deep learning (DL) methods that rely on region-of-interest (ROI) annotations yield models that fail to generalize to unrelated datasets. Newer unsupe...
Advancements in volume electron microscopy mean it is now possible to generate thousands of serial images at nanometre resolution overnight, yet the gold standard approach for data analysis remains manual segmentation by an expert microscopist, resul...