A medical image segmentation method for GFC-MSPCNN

Na Zhang; Jinyu Zhang; Qin Zhou; Yuzhu Cao; Jing Lian

doi:10.1117/12.3035151

19 July 2024 A medical image segmentation method for GFC-MSPCNN

Na Zhang, Jinyu Zhang, Qin Zhou, Yuzhu Cao, Jing Lian

Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 1321310 (2024) https://doi.org/10.1117/12.3035151
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China

Abstract

Medical image segmentation has an important role in medical diagnosis, clinical and other social reality scenes, and it is very important significance to reasonably analyze medical images. pulse-coupled neural network (PCNN) has great potential for artificial neural networks with biological background. In this paper, we propose a medical image segmentation method based on a Global fire-controlled MSPCNN (GFC-MSPCNN) in terms of the influence of neurons. The proposed method improve the interaction between the central neurons and their near-neighboring neurons, which is more suitable for human visual characteristics. It is evident from the experiment that the proposed method can obviously reduce the detection cost and improve the detection accuracy, which is an effective medical image segmentation method.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Na Zhang, Jinyu Zhang, Qin Zhou, Yuzhu Cao, and Jing Lian "A medical image segmentation method for GFC-MSPCNN", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 1321310 (19 July 2024); https://doi.org/10.1117/12.3035151

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