Urine sediment image recognition method based on re-parameterization network

Zhangwei Wu; Qingbo Ji

doi:10.1117/12.2631837

14 April 2022 Urine sediment image recognition method based on re-parameterization network

Zhangwei Wu, Qingbo Ji

Proceedings Volume 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021); 121780B (2022) https://doi.org/10.1117/12.2631837
Event: International Conference on Signal Processing and Communication Technology (SPCT 2021), 2021, Tianjin, China

Abstract

Urine routine examination has moved towards automation in recent years. In order to improve the accuracy and recognition speed of the automatic urine analyzer, a urine sediment classification method based on the attention mechanism and reparameterization is proposed. Aiming at the problem of unclear images of some urine sediments and noise, image processing technology is used to pre-processed. Aiming at the problem of some classes are easy to be confused in classification, during network training, multiple branches are used for feature extraction, and the attention mechanism is used to focus on the key points in the image, which improves the accuracy of easily confused classes. Multi-branch can be equivalently replaced with a single branch during inference to improve the recognition speed. Experimental results show that the designed network can effectively improve the classification accuracy of urine sediment images.

Citation Download Citation

Zhangwei Wu and Qingbo Ji "Urine sediment image recognition method based on re-parameterization network", Proc. SPIE 12178, International Conference on Signal Processing and Communication Technology (SPCT 2021), 121780B (14 April 2022); https://doi.org/10.1117/12.2631837

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KEYWORDS

Image classification

Image processing

Data modeling

Image enhancement

Blood

Network architectures

Chemical analysis

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