AIMC Topic: Microscopy
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Microscopy Image Dataset for Deep Learning-Based Quantitative Assessment of Pulmonary Vascular Changes.
Scientific data
Jun 15, 2024
Pulmonary hypertension (PH) is a syndrome complex that accompanies a number of diseases of different etiologies, associated with basic mechanisms of structural and functional changes of the pulmonary circulation vessels and revealed pressure increasi...
AI analysis of super-resolution microscopy: Biological discovery in the absence of ground truth.
The Journal of cell biology
Jun 12, 2024
Super-resolution microscopy, or nanoscopy, enables the use of fluorescent-based molecular localization tools to study molecular structure at the nanoscale level in the intact cell, bridging the mesoscale gap to classical structural biology methodolog...
A Review of Nuclei Detection and Segmentation on Microscopy Images Using Deep Learning With Applications to Unbiased Stereology Counting.
IEEE transactions on neural networks and learning systems
Jun 3, 2024
The detection and segmentation of stained cells and nuclei are essential prerequisites for subsequent quantitative research for many diseases. Recently, deep learning has shown strong performance in many computer vision problems, including solutions ...
A deep learning-based model for detecting Leishmania amastigotes in microscopic slides: a new approach to telemedicine.
BMC infectious diseases
Jun 1, 2024
BACKGROUND: Leishmaniasis, an illness caused by protozoa, accounts for a substantial number of human fatalities globally, thereby emerging as one of the most fatal parasitic diseases. The conventional methods employed for detecting the Leishmania par...
AI-powered microscopy image analysis for parasitology: integrating human expertise.
Trends in parasitology
May 31, 2024
Microscopy image analysis plays a pivotal role in parasitology research. Deep learning (DL), a subset of artificial intelligence (AI), has garnered significant attention. However, traditional DL-based methods for general purposes are data-driven, oft...
Rapid and Precise Diagnosis of Retroperitoneal Liposarcoma with Deep-Learned Label-Free Molecular Microscopy.
Analytical chemistry
May 29, 2024
The retroperitoneal liposarcoma (RLPS) is a rare malignancy whose only curative therapy is surgical resection. However, well-differentiated liposarcomas (WDLPSs), one of its most common types, can hardly be distinguished from normal fat during operat...
Objectification of evaluation criteria in microscopic agglutination test using deep learning.
Journal of microbiological methods
May 14, 2024
We aim to objectify the evaluation criteria of agglutination rate estimation in the Microscopic Agglutination Test (MAT). This study proposes a deep learning method that extracts free leptospires from dark-field microscopic images and calculates the ...
Microscope-integrated optical coherence tomography for in vivo human brain tumor detection with artificial intelligence.
Journal of neurosurgery
May 3, 2024
OBJECTIVE: It has been shown that optical coherence tomography (OCT) can identify brain tumor tissue and potentially be used for intraoperative margin diagnostics. However, there is limited evidence on its use in human in vivo settings, particularly ...
Real-time 3D tracking of swimming microbes using digital holographic microscopy and deep learning.
PloS one
Apr 26, 2024
The three-dimensional swimming tracks of motile microorganisms can be used to identify their species, which holds promise for the rapid identification of bacterial pathogens. The tracks also provide detailed information on the cells' responses to ext...
Model-free robust motion control for biological optical microscopy using time-delay estimation with an adaptive RBFNN compensator.
ISA transactions
Apr 22, 2024
The field of large numerical aperture microscopy has witnessed significant advancements in spatial and temporal resolution, as well as improvements in optical microscope imaging quality. However, these advancements have concurrently raised the demand...
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