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Detection of Micro Plastics in Human Lung Tissues: Using Matlab-Based CNN
Summary
This study developed a MATLAB-based convolutional neural network approach to detect microplastics in human lung tissue images from CT or microscopy scans. The system combined image enhancement, region-of-interest extraction, and CNN classification to identify plastic particle presence with high detection accuracy.
The smaller particles found in the surrounding, are smaller in size 5mm or less, commonly known as Microplastics. These small residues can enter human body through respiration, ingestion and also sometimes through exposure and wounds. These particle infusions in human beings is raising serious concern and having harmful effects on human body. Now-a-days these particles are commonly found in human organs that leads to future health issues. This study focus on detection of Micro-plastics in human lungs using approach based on Matlab. In this paper, the convolutional neural network process is combined with image-processing methods to detect the presence of microplastics in human tissue. The detection involves several steps including: enhancement of image, region of interest extraction and performance analysis of methodology. The motive of this study is to reduce the manual work and using technology in prominent ways.
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