A medical image segmentation method based on SGFC-MSPCNN

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

doi:10.1117/12.3035130

19 July 2024 A medical image segmentation method based on SGFC-MSPCNN

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

Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 132130V (2024) https://doi.org/10.1117/12.3035130
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China

Abstract

In recent years, pulse-coupled neural network (PCNN) has been widely used in the image segmentation field and has obtained relatively satisfactory results. In this paper, based on fire-controlled MSPCNN(FC-MSPCNN), an image segmentation method based on saliency-guided FCMSPCNN(SGFC-MSPCNN) is proposed, which enhances the reasonableness of the variations between the internal activity term and dynamic threshold for the proposed model. and after experimental validation, the method significantly improves the detection accuracy while reducing the detection cost, and thus it is confirmed to be an effective medical image segmentation method.

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

Citation Download Citation

Jinyu Zhang, Qin Zhou, Na Zhang, Yuzhu Cao, and Jing Lian "A medical image segmentation method based on SGFC-MSPCNN", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 132130V (19 July 2024); https://doi.org/10.1117/12.3035130

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