ArticleRSC advances2023
Deep learning for automated size and shape analysis of nanoparticles in scanning electron microscopy.
Article in RSC advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 68 citations in OpenAlex.
- Cancer Drug Delivery with Nanoparticles and Biomolecules: Stimuli-Responsive, Theranostic, and AI-Guided Approaches.Materials (Basel, Switzerland) · 2026Review
- Nanosphere Self-Assembly Imaging Systems and Defect Detection Algorithms for Self-Assembled Structures: A Review.Nanomaterials (Basel, Switzerland) · 2026Review
- Enhanced Activity of Leather Materials Coated with Silver, Copper and Graphene Oxides-Decorated TiOMaterials (Basel, Switzerland) · 2026Article
- Few-shot learning for classification of SEM images from green-synthesized nanoparticles of Momordica cymbalaria.Scientific reports · 2026Article
- AI-driven nanomedicine for cancer theranostics.Molecular cancer · 2026Review
- Smart Nanomedicines for Neurodegenerative Diseases: Empowering New Therapies with Molecular Imaging and Artificial Intelligence.Molecular diagnosis & therapy · 2026Review
- Automated Particle Size Analysis of Supported Nanoparticle TEM Images Using a Pre-Trained SAM Model.Nanomaterials (Basel, Switzerland) · 2025Article
- Machine Learning Approaches in Soft Matter Molecular Simulation and Materials Characterization: Challenges and Perspectives.ChemPlusChem · 2025Article
- Silver integrated hybrids and nanocomposites for next-generation biomedicine: Beyond antimicrobial coatings toward smart sense-response-heal platforms.Materials today. Bio · 2025Review
- Nanomaterials in Drug Delivery: Leveraging Artificial Intelligence and Big Data for Predictive Design.International journal of molecular sciences · 2025Review
- Workflow and Practical Guidance for Identical Location Scanning Electron Microscopy: Reliable Tracking of Localized Transformations.Small methods · 2025Article
- SEMTWIST Quantification of Biofilm Infection in Human Chronic Wound Using Scanning Electron Microscopy and Machine Learning.Advances in wound care · 2025Article
- ResNet-based image processing approach for precise detection of cracks in photovoltaic panels.Scientific reports · 2025Article
- Dihydroartemisinin-sodium taurocholate-PLGA nanoparticles: a novel therapeutic approach against cystic echinococcosis.Frontiers in pharmacology · 2025Article
- Nanotoxicology: developments and new insights.Nanomedicine (London, England) · 2025Review
- Adding More Shape to Nanoscale Reference Materials─LiYFAnalytical chemistry · 2024Article
- Size-Resolved Shape Evolution in Inorganic Nanocrystals Captured via High-Throughput Deep Learning-Driven Statistical Characterization.ACS nano · 2024Article
- Morphological analysis of Pd/C nanoparticles using SEM imaging and advanced deep learning.RSC advances · 2024Article
- Exploiting Temporal Features in Calculating Automated Morphological Properties of Spiky Nanoparticles Using Deep Learning.Sensors (Basel, Switzerland) · 2024Article
- Characterization of Particle Shape with an Improved 3D Light Scattering Sensor (3D-LSS) for Aerosols.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The automated analysis of nanoparticles, imaged by scanning electron microscopy, was implemented by a deep-learning (artificial intelligence) procedure based on convolutional neural networks (CNNs). It is possible to extract quantitative information on particle size distributions and particle shapes from pseudo-three-dimensional secondary electron micrographs (SE) as well as from two-dimensional scanning transmission electron micrographs (STEM). After separation of particles from the background (segmentation), the particles were cut out from the image to be classified by their shape (
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.