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Spectrometry, Mass, Secondary Ion

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Surface Adsorbed Antibody Characterization Using ToF-SIMS with Principal Component Analysis and Artificial Neural Networks.

Langmuir : the ACS journal of surfaces and colloids
Artificial neural networks (ANNs) form a class of powerful multivariate analysis techniques, yet their routine use in the surface analysis community is limited. Principal component analysis (PCA) is more commonly employed to reduce the dimensionality...

Time-of-flight secondary ion mass spectrometry analysis of hair samples using unsupervised artificial neural network.

Biointerphases
Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is extensively employed for the structural analysis of the outermost surfaces of organic materials, including biological materials, because it provides detailed compositional information and e...

Analyzing 3D hyperspectral TOF-SIMS depth profile data using self-organizing map-relational perspective mapping.

Biointerphases
The advantages of applying multivariate analysis to mass spectrometry imaging (MSI) data have been thoroughly demonstrated in recent decades. The identification and visualization of complex relationships between pixels in a hyperspectral data set can...

Revealing Contamination and Sequence of Overlapping Fingerprints by Unsupervised Treatment of a Hyperspectral Secondary Ion Mass Spectrometry Dataset.

Analytical chemistry
Time-of-flight secondary ion mass spectrometry (ToF-SIMS) has been successfully applied for chemical imaging of overlapping fingermarks. The resulting big dataset has been treated by means of an unsupervised machine learning approach based on uniform...

Applications of multivariate analysis and unsupervised machine learning to ToF-SIMS images of organic, bioorganic, and biological systems.

Biointerphases
Time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging offers a powerful, label-free method for exploring organic, bioorganic, and biological systems. The technique is capable of very high spatial resolution, while also producing an enormo...

Two-Dimensional and Three-Dimensional Time-of-Flight Secondary Ion Mass Spectrometry Image Feature Extraction Using a Spatially Aware Convolutional Autoencoder.

Analytical chemistry
Feature extraction algorithms are an important class of unsupervised methods used to reduce data dimensionality. They have been applied extensively for time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging─commonly, matrix factorization (...

Automated Single Cell Phenotyping of Time-of-Flight Secondary Ion Mass Spectrometry Tissue Images.

Journal of the American Society for Mass Spectrometry
Existing analytical techniques are being improved or applied in new ways to profile the tissue microenvironment (TME) to better understand the role of cells in disease research. Fully understanding the complex interactions between cells of many diffe...

Machine Learning Correlation of Electron Micrographs and ToF-SIMS for the Analysis of Organic Biomarkers in Mudstone.

Journal of the American Society for Mass Spectrometry
The spatial distribution of organics in geological samples can be used to determine when and how these organics were incorporated into the host rock. Mass spectrometry (MS) imaging can rapidly collect a large amount of data, but ions produced are mix...

Development of Peptide Identification System for ToF-SIMS Spectra Using Supervised Machine Learning.

Journal of the American Society for Mass Spectrometry
Time-of-flight secondary ion mass spectrometry (ToF-SIMS) data interpretation for organic materials is complicated because of various fragment ions produced from each molecule and the overlapping of certain mass peaks from different molecules. Fragme...