Novel low-dispersion ablation cell designs and highly efficient aerosol transport systems have enabled fast elemental mapping using laser ablation-ICP-mass spectrometry (LA-ICP-MS) at high spatial resolution and its application in various research fields. Nowadays, the fastest low-dispersion setups enable narrow single pulse responses (SPR, duration of the transient signal observed upon a single laser shot), which enhance the signal-to-noise ratio and boost the pixel acquisition rate attainable in elemental mapping applications. In this work, the analytical performance of a nanosecond 193 nm ArF* excimer-based kHz laser in combination with a low-dispersion tube-type ablation cell, coupled to an ICP-mass spectrometer equipped with a time-of-flight (ToF) analyzer, was evaluated. SPR profiles exhibited a duration below 1 ms (defined as full peak width at 10% of the peak maximum, FW0.1M) upon ablation of a NIST SRM 610 glass reference material (0.7 ± 0.1 ms) and a multielement-spiked gelatin droplet standard (0.6 ± 0.1 ms) using a 5 μm laser spot size and matrix-optimized laser energy density. Parameters such as pulse-to-pulse energy stability, linearity of the signal response, oxide ion formation, and elemental fractionation were evaluated. The duration of the SPR profiles determines the maximum achievable pixel acquisition rate, enabling up to 1000 pixels/s with the setup evaluated. As a proof of concept, this is illustrated via quantitative multielemental mapping of a highly primitive chondritic meteorite, displaying a fine mineral texture and heterogeneous elemental distributions, at high spatial resolution and firing only a single shot per pixel.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1021/acs.analchem.4c05667 | DOI Listing |
Anal Chem
March 2025
Department of Chemistry, Atomic and Mass Spectrometry - A&MS Research Group, Ghent University, Campus Sterre, Krijgslaan 281-S12, Ghent 9000, Belgium.
Novel low-dispersion ablation cell designs and highly efficient aerosol transport systems have enabled fast elemental mapping using laser ablation-ICP-mass spectrometry (LA-ICP-MS) at high spatial resolution and its application in various research fields. Nowadays, the fastest low-dispersion setups enable narrow single pulse responses (SPR, duration of the transient signal observed upon a single laser shot), which enhance the signal-to-noise ratio and boost the pixel acquisition rate attainable in elemental mapping applications. In this work, the analytical performance of a nanosecond 193 nm ArF* excimer-based kHz laser in combination with a low-dispersion tube-type ablation cell, coupled to an ICP-mass spectrometer equipped with a time-of-flight (ToF) analyzer, was evaluated.
View Article and Find Full Text PDFSci Data
March 2025
Medical AI Lab, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, 518060, China.
Inflammatory bowel disease (IBD) is a recurrent bowel disease that usually requires magnetic resonance enterography (MRE) for diagnosis and monitoring. However, recognition of bowel segments from MRE images by a radiologist is challenging and time-consuming. Deep learning-based medical image segmentation has shown the potential to reduce manual effort and provide automated tools to assist in disease management; however, it requires a large-scale fine-annotated dataset for training.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2024
Medical image segmentation using deep learning typically requires a large quantity of well-annotated data. However, the acquisition of pixel-level annotations is arduous and expensive, often requiring the expertise of experienced medical professionals. Recent advancements in few-shot learning can help address label scarcity in medical image segmentation by leveraging a small amount of labeled data.
View Article and Find Full Text PDFThis article derives and implements a computational physics model for model-based image reconstruction in magnetic particle imaging (MPI) applications. To our knowledge, this is the first ever computationally tractable model-based image reconstruction in MPI, which is neither constructed from calibration or simulation experiments or limited to specific scan acquisition geometries. The derived model results in a system constructed from a series of fast linear transforms, each of which incorporate the individual components from the paramagnetic model.
View Article and Find Full Text PDFTissue semantic segmentation is one of the key tasks in computational pathology. To avoid the expensive and laborious acquisition of pixel-level annotations, a wide range of studies attempt to adopt the class activation map (CAM), a weakly-supervised learning scheme, to achieve pixel-level tissue segmentation. However, CAM-based methods are prone to suffer from under-activation and over-activation issues, leading to poor segmentation performance.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!