article · Frontiers in Oncology · 2024
A deep learning-based cascade algorithm for pancreatic tumor segmentation
Dandan Qiu, Jianguo Ju, Shumin Ren, Tongtong Zhang, Huijuan Tu, Xin Tan, Fei Xie
Cited by 8Open access
Abstract
Pancreatic tumors are small in size, diverse in shape, and have low contrast and high texture similarity with surrounding tissue. As a result, the segmentation model is easily confused by complex and changeable background information, leading to inaccurate positioning of small targets and false positives and false negatives. Therefore, we design a cascaded pancreatic tumor segmentation algorithm. In the first stage, we use a general multi-scale U-Net to segment the pancreas, and we exploit a multi-scale segmentation network based on non-local localization and focusing modules to segment pancreatic tumors in the second stage. The non-local localization module learns channel and spatial position information, searches for the approximate area where the pancreatic tumor is located from a global perspective, and obtains the initial segmentation results. The focusing module conducts context exploration based on foreground features (or background features), detects and removes false positive (or false negative) interference, and obtains more accurate segmentation results based on the initial segmentation. In addition, we design a new loss function to alleviate the insensitivity to small targets. Experimental results show that the proposed algorithm can more accurately locate pancreatic tumors of different sizes, and the Dice coefficient outperforms the existing state-of-the-art segmentation model. The code will be available at https://github.com/HeyJGJu/Pancreatic-Tumor-SEG.
Cite this paper
Qiu, D., Ju, J., Ren, S., Zhang, T., Tu, H., Tan, X., & Xie, F. (2024). A deep learning-based cascade algorithm for pancreatic tumor segmentation. Frontiers in Oncology, 14, 1328146. https://doi.org/10.3389/fonc.2024.1328146
Qiu, Dandan, et al. “A deep learning-based cascade algorithm for pancreatic tumor segmentation.” Frontiers in Oncology, vol. 14, 2024, p. 1328146, https://doi.org/10.3389/fonc.2024.1328146.
Qiu, Dandan, Jianguo Ju, Shumin Ren, Tongtong Zhang, Huijuan Tu, Xin Tan, and Fei Xie. 2024. “A deep learning-based cascade algorithm for pancreatic tumor segmentation.” Frontiers in Oncology 14: 1328146. https://doi.org/10.3389/fonc.2024.1328146.
Qiu, D. et al. (2024) ‘A deep learning-based cascade algorithm for pancreatic tumor segmentation’, Frontiers in Oncology, 14, p. 1328146. Available at: https://doi.org/10.3389/fonc.2024.1328146.
@article{qiu2024deep,
title = {{A deep learning-based cascade algorithm for pancreatic tumor segmentation}},
author = {Qiu, Dandan and Ju, Jianguo and Ren, Shumin and Zhang, Tongtong and Tu, Huijuan and Tan, Xin and Xie, Fei},
journal = {Frontiers in Oncology},
volume = {14},
pages = {1328146},
year = {2024},
doi = {10.3389/fonc.2024.1328146}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.