AIMC Topic: Microscopy

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Study on identification algorithm of traditional Chinese medicinals microscopic image based on convolutional neural network.

Medicine Jun 23, 2023
UNLABELLED: When the similarity of medicinal materials is high and easily confused, the traditional subjective judgment has an impact on the identification results. Use high-dimensional features to identify medicinal materials to ensure the quality o...
Neural Networks, Computer Algorithms Drugs, Chinese Herbal Microscopy Powders
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Neuron tracing from light microscopy images: automation, deep learning and bench testing.

Bioinformatics (Oxford, England) Dec 13, 2022
MOTIVATION: Large-scale neuronal morphologies are essential to neuronal typing, connectivity characterization and brain modeling. It is widely accepted that automation is critical to the production of neuronal morphology. Despite previous survey pape...
Algorithms Animals Deep Learning Imaging, Three-Dimensional Neurons Mammals Microscopy Automation
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Fourier ptychographic microscopy with untrained deep neural network priors.

Optics express Oct 24, 2022
We propose a physics-assisted deep neural network scheme in Fourier ptychographic microscopy (FPM) using untrained deep neural network priors (FPMUP) to achieve a high-resolution image reconstruction from multiple low-resolution images. Unlike the tr...
Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Microscopy Fourier Analysis
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Sparse phase retrieval using a physics-informed neural network for Fourier ptychographic microscopy.

Optics letters Oct 1, 2022
In this paper, we report a sparse phase retrieval framework for Fourier ptychographic microscopy using the recently proposed principle of physics-informed neural networks. The phase retrieval problem is cast as training bidirectional mappings from th...
Neural Networks, Computer Microscopy
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Deep-SMOLM: deep learning resolves the 3D orientations and 2D positions of overlapping single molecules with optimal nanoscale resolution.

Optics express Sep 26, 2022
Dipole-spread function (DSF) engineering reshapes the images of a microscope to maximize the sensitivity of measuring the 3D orientations of dipole-like emitters. However, severe Poisson shot noise, overlapping images, and simultaneously fitting high...
Deep Learning Image Processing, Computer-Assisted Nanotechnology Microscopy Amyloid
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Deep-learning for microscopy.

Nature cell biology Sep 1, 2022
Deep Learning Image Processing, Computer-Assisted Microscopy
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Lensless computational imaging with a hybrid framework of holographic propagation and deep learning.

Optics letters Sep 1, 2022
Lensless imaging has attracted attention as it avoids the bulky optical lens. Lensless holographic imaging is a type of a lensless imaging technique. Recently, deep learning has also shown tremendous potential in lensless holographic imaging. A label...
Deep Learning Lenses Microscopy Holography
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Single-frame 3D lensless microscopic imaging via deep learning.

Optics express Aug 29, 2022
Since the pollen of different species varies in shape and size, visualizing the 3-dimensional structure of a pollen grain can aid in its characterization. Lensless sensing is useful for reducing both optics footprint and cost, while the capability to...
Neural Networks, Computer Deep Learning Imaging, Three-Dimensional Microscopy Pollen
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Single-exposure height-recovery structured illumination microscopy based on deep learning.

Optics letters Aug 1, 2022
Modulation-based structured illumination microscopy (SIM) is performed to reconstruct three-dimensional (3D) surface topography. Generally speaking, modulation decoding algorithms mainly include a phase-shift (PS) method and frequency analysis techni...
Neural Networks, Computer Algorithms Deep Learning Lighting Microscopy
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A Cascaded Deep Learning Framework for Segmentation of Nuclei in Digital Histology Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Accurate segmentation of nuclei is an essential step in analysis of digital histology images for diagnostic and prognostic applications. Despite recent advances in automated frameworks for nuclei segmentation, this task is still challenging. Specific...
Neural Networks, Computer Deep Learning Microscopy Cell Nucleus Histological Techniques
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