Bone tumor boundary demarcation based on multimodal image fusion

Ruizhe Shang; Jiaming Dong; Xinhuai Wang

doi:10.1117/12.3055913

9 January 2025 Bone tumor boundary demarcation based on multimodal image fusion

Ruizhe Shang, Jiaming Dong, Xinhuai Wang

Author Affiliations +

Proceedings Volume 13486, Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024); 134860W (2025) https://doi.org/10.1117/12.3055913
Event: Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024), 2024, Chengdu, China

Abstract

The delineation of bone tumor boundaries is a critical issue in the field of medical image segmentation due to the unique positioning of these tumors and the complexity of the associated surgical procedures. In recent years, researchers have made significant strides in determining tumor boundaries through computer version methods. Doctors can achieve precise localization of bone tumors using the U-Net network or the improvements. However, using tumor boundary segmentation models based on single-modal images makes it challenging to capture the complete characteristics of the tumor. In this paper, we propose a multi-modal image fusion network to achieve more accurate segmentation of tumor boundaries. Experimental results show that the accuracy of the segmentation results can be improved by about 6.8% when using fused images for segmentation. Therefore, this image processing process is of great significance for improving the accuracy of bone tumor boundary demarcation and the efficiency of clinical diagnosis.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ruizhe Shang, Jiaming Dong, and Xinhuai Wang "Bone tumor boundary demarcation based on multimodal image fusion", Proc. SPIE 13486, Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024), 134860W (9 January 2025); https://doi.org/10.1117/12.3055913

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