AIMC Topic: Microscopy, Fluorescence

Clear Filters Showing 121 to 130 of 205 articles

DeLTA: Automated cell segmentation, tracking, and lineage reconstruction using deep learning.

PLoS computational biology
Microscopy image analysis is a major bottleneck in quantification of single-cell microscopy data, typically requiring human oversight and curation, which limit both accuracy and throughput. To address this, we developed a deep learning-based image an...

A mitochondria-targeting nitroreductase fluorescent probe with large Stokes shift and long-wavelength emission for imaging hypoxic status in tumor cells.

Analytica chimica acta
Development of a mitochondria-targeting fluorescent probe with large Stokes shift and long-wavelength emission was benefit for accurate detection of hypoxic status, which was known as a major factor of the tumor physiology and influence important pat...

Super-Soft and Super-Elastic DNA Robot with Magnetically Driven Navigational Locomotion for Cell Delivery in Confined Space.

Angewandte Chemie (International ed. in English)
Soft organisms such as earthworms can access confined, narrow spaces, inspiring scientists to fabricate soft robots for in vivo manipulation of cells or tissues and minimally invasive surgery. We report a super-soft and super-elastic magnetic DNA hyd...

AI-powered transmitted light microscopy for functional analysis of live cells.

Scientific reports
Transmitted light microscopy can readily visualize the morphology of living cells. Here, we introduce artificial-intelligence-powered transmitted light microscopy (AIM) for subcellular structure identification and labeling-free functional analysis of...

Robust blind spectral unmixing for fluorescence microscopy using unsupervised learning.

PloS one
Due to the overlapping emission spectra of fluorophores, fluorescence microscopy images often have bleed-through problems, leading to a false positive detection. This problem is almost unavoidable when the samples are labeled with three or more fluor...

Analysis of the Human Protein Atlas Image Classification competition.

Nature methods
Pinpointing subcellular protein localizations from microscopy images is easy to the trained eye, but challenging to automate. Based on the Human Protein Atlas image collection, we held a competition to identify deep learning solutions to solve this t...

Deep-UV excitation fluorescence microscopy for detection of lymph node metastasis using deep neural network.

Scientific reports
Deep-UV (DUV) excitation fluorescence microscopy has potential to provide rapid diagnosis with simple technique comparing to conventional histopathology based on hematoxylin and eosin (H&E) staining. We established a fluorescent staining protocol for...

Three-dimensional virtual refocusing of fluorescence microscopy images using deep learning.

Nature methods
We demonstrate that a deep neural network can be trained to virtually refocus a two-dimensional fluorescence image onto user-defined three-dimensional (3D) surfaces within the sample. Using this method, termed Deep-Z, we imaged the neuronal activity ...

MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation.

Neural networks : the official journal of the International Neural Network Society
In recent years Deep Learning has brought about a breakthrough in Medical Image Segmentation. In this regard, U-Net has been the most popular architecture in the medical imaging community. Despite outstanding overall performance in segmenting multimo...

Support Vector Machine Classification of Nonmelanoma Skin Lesions Based on Fluorescence Lifetime Imaging Microscopy.

Analytical chemistry
Early diagnosis of malignant skin lesions is critical for prompt treatment and a clinical prognosis of skin cancers. However, it is difficult to precisely evaluate the development stage of nonmelanoma skin cancers because they are derived from the sa...