AIMC Topic: Lasers

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Machine Learning-Assisted Multimodal Early Screening of Lung Cancer Based on a Multiplexed Laser-Induced Graphene Immunosensor.

ACS nano
Lung cancer remains the leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis. Early detection is critical for improving patient outcomes, yet current screening methods, such as low-dose computed tomography (CT), of...

Combined impact of semantic segmentation and quantitative structure modelling of Southern pine trees using terrestrial laser scanning.

Scientific reports
Southern pine forests play a key role in the ecological function and economic vitality of the southeastern United States. High-resolution terrestrial laser scanning (TLS) has become an indispensable tool for advancing tree structural research and mon...

Femtosecond laser-assisted printing of hard magnetic microrobots for swimming upstream in subcentimeter-per-second blood flow.

Science advances
Magnetic microrobots have garnered increasing attention in the biomedical field due to their wireless motion control and noninvasive therapeutic potential. However, current microrobots fabricated from soft magnetic materials exhibit critical limitati...

Detection of whey protein concentrate adulteration using laser-induced breakdown spectroscopy combined with machine learning.

Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment
In recent years, food fraud issues related to whey protein supplements have disrupted the market and caused significant concern among consumers. Conventional analytical methods such as HPLC and ion exchange chromatography are commonly used to detect ...

Identification of cancerous tissues based on residual neural network.

Scientific reports
The identification of cancerous tissues remains challenging due to the complexity of experimental methods and low identification accuracy rates. Therefore, this paper proposes a rapid identification method. We introduce a new theoretical transmission...

Efficient and anti-interference plastic classification method suitable for one-shot learning based on laser induced breakdown spectroscopy.

Chemosphere
Efficient recycling of plastics is critical for environmental sustainability. In this work, an efficient and anti-interference method for plastic classification based on one-shot learning and laser-induced breakdown spectroscopy (LIBS) was proposed. ...

DMC-LIBSAS: A Laser-Induced Breakdown Spectroscopy Analysis System with Double-Multi Convolutional Neural Network for Accurate Traceability of Chinese Medicinal Materials.

Sensors (Basel, Switzerland)
Against the background of globalization, the circulation range of traditional Chinese medicinal materials is constantly expanding, and the phenomena of mixed origins and counterfeiting are becoming increasingly serious. Tracing the origin of traditio...

Robust Human Tracking Using a 3D LiDAR and Point Cloud Projection for Human-Following Robots.

Sensors (Basel, Switzerland)
Human tracking is a fundamental technology for mobile robots that work with humans. Various devices are used to observe humans, such as cameras, RGB-D sensors, millimeter-wave radars, and laser range finders (LRF). Typical LRF measurements observe on...

Label-free rapid antimicrobial susceptibility testing with machine-learning based dynamic holographic laser speckle imaging.

Biosensors & bioelectronics
Antimicrobial resistance (AMR) presents a significant global challenge, creating an urgent need for rapid and sensitive antimicrobial susceptibility testing (AST) methods to guide timely treatment decisions. Traditional AST techniques, such as broth ...

Development of a method for detecting and classifying hydrocarbon-contaminated soils via laser-induced breakdown spectroscopy and machine learning algorithms.

Environmental science and pollution research international
In recent years, there has been a significant increase in oil exploration and exploitation activities, resulting in spills that pose a severe threat to the environment and public health. The present work aims to develop a method to detect and classif...