AIMC Topic: Microscopy, Fluorescence
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Machine learning approach for discrimination of genotypes based on bright-field cellular images.
NPJ systems biology and applications
Jul 21, 2021
Morphological profiling is a combination of established optical microscopes and cutting-edge machine vision technologies, which stacks up successful applications in high-throughput phenotyping. One major question is how much information can be extrac...
Asbestos Detection with Fluorescence Microscopy Images and Deep Learning.
Sensors (Basel, Switzerland)
Jul 4, 2021
Fluorescent probes can be used to detect various types of asbestos (serpentine and amphibole groups); however, the fiber counting using our previously developed software was not accurate for samples with low fiber concentration. Machine learning-base...
Use of Convolutional Neural Networks for the Detection of u-Serrated Patterns in Direct Immunofluorescence Images to Facilitate the Diagnosis of Epidermolysis Bullosa Acquisita.
The American journal of pathology
Jun 28, 2021
The u-serrated immunodeposition pattern in direct immunofluorescence (DIF) microscopy is a recognizable feature and confirmative for the diagnosis of epidermolysis bullosa acquisita (EBA). Due to unfamiliarity with serrated patterns, serration patter...
Application of convolutional neural networks towards nuclei segmentation in localization-based super-resolution fluorescence microscopy images.
BMC bioinformatics
Jun 15, 2021
BACKGROUND: Automated segmentation of nuclei in microscopic images has been conducted to enhance throughput in pathological diagnostics and biological research. Segmentation accuracy and speed has been significantly enhanced with the advent of convol...
Deep probabilistic tracking of particles in fluorescence microscopy images.
Medical image analysis
Jun 8, 2021
Tracking of particles in temporal fluorescence microscopy image sequences is of fundamental importance to quantify dynamic processes of intracellular structures as well as virus structures. We introduce a probabilistic deep learning approach for fluo...
A Preliminary Study of Deep-Learning Algorithm for Analyzing Multiplex Immunofluorescence Biomarkers in Body Fluid Cytology Specimens.
Acta cytologica
Jun 2, 2021
INTRODUCTION: Multiplex biomarker analysis of cytological body fluid specimens is often used to assist cytologists in distiguishing metastatic cancer cells from reactive mesothelial cells. However, evaluating biomarker expression visually may be chal...
Cytodiagnosis
Microscopy, Fluorescence
Deep Learning
Reproducibility of Results
Pleural Effusion, Malignant
Adenocarcinoma
Biomarkers, Tumor
Image Processing, Computer-Assisted
Humans
Diagnosis, Differential
Feasibility Studies
Fluorescent Antibody Technique
Diagnosis, Computer-Assisted
Retrospective Studies
Predictive Value of Tests
Neural network strategies for plasma membrane selection in fluorescence microscopy images.
Biophysical journal
May 4, 2021
In recent years, there has been an explosion of fluorescence microscopy studies of live cells in the literature. The analysis of the images obtained in these studies often requires labor-intensive manual annotation to extract meaningful information. ...
Improving axial resolution in Structured Illumination Microscopy using deep learning.
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Apr 26, 2021
Structured Illumination Microscopy (SIM) is a widespread methodology to image live and fixed biological structures smaller than the diffraction limits of conventional optical microscopy. Using recent advances in image up-scaling through deep learning...
Magnetically Actuated Drug Delivery Helical Microrobot with Magnetic Nanoparticle Retrieval Ability.
ACS applied materials & interfaces
Apr 20, 2021
Therapeutic drug delivery microrobots capable of accurate targeting using an electromagnetic actuation (EMA) system are being developed. However, these drug delivery microrobots include a large number of magnetic nanoparticles (MNPs) for accurate EMA...
Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning.
PLoS computational biology
Feb 22, 2021
Phenotypic profiling of large three-dimensional microscopy data sets has not been widely adopted due to the challenges posed by cell segmentation and feature selection. The computational demands of automated processing further limit analysis of hard-...
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