Article

A deep learning approach for improving two-photon vascular imaging speeds

2022-12-02

Abstract excerpt

A potential method for tracking neurovascular disease progression over time in preclinical models is multiphoton fluorescence microscopy (MPM), which can image cerebral vasculature with capillary-level resolution. However, obtaining high-quality, three-dimensional images with a traditional point scanning MPM is time-consuming and limits sample sizes for chronic studies. Here, we present a convolutional neural netw...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 2e5dbab3-b591-5321-a363-3cd5ae79a4a4
DOI: 10.1101/2022.11.30.518528

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A deep learning approach for improving two-photon vascular imaging speedsDOI 10.1101/2022.11.30.518528Read

Anatomical modeling of brain vasculature in two-photon microscopy by generalizable deep learningSemantic proximity Read

Physics-informed deep generative learning for quantitative assessment of the retinaSemantic proximity Read

3DVascNet: an automated software for segmentation and quantification of vascular networks in 3DSemantic proximity Read

tUbe net: a generalisable deep learning tool for 3D vessel segmentationSemantic proximity Read

Segmentation-less, automated vascular vectorization robustly extracts neurovascular network statistics from in vivo two-photon imagesSemantic proximity Read

Label-free phenotyping of human microvessel networksSemantic proximity Read

Dual-Field Microvascular Segmentation: Hemodynamically-Consistent Attention Learning for Retinal Vasculature MappingSemantic proximity Read

Unsupervised segmentation of 3D microvascular photoacoustic images using deep generative learningSemantic proximity Read

Near-lifespan longitudinal tracking of brain microvascular morphology, topology, and flow in male miceSemantic proximity Read

Cerebrovascular super-resolution 4D Flow MRI – using deep learning to non-invasively quantify velocity, flow, and relative pressureSemantic proximity Read

Deep Learning of the Retina Enables Phenome- and Genome-Wide Analyses of the MicrovasculatureSemantic proximity Read

Deep Learning Enables Genome-Wide Association Studies of Microvascular FeaturesSemantic proximity Read