Application of Improved Wild Horse Optimizer Based on Chaos Initialization in Medical Image Segmentation

Author:

Li LinguoORCID,Zhang Mingyu,Li Qinghe,Li ShujingORCID

Publisher

Springer Nature Singapore

Reference17 articles.

1. Liu, S., Wang, H., Li, Y., et al.: AHU-MultiNet: adaptive loss balancing based on homoscedastic uncertainty in multi-task medical image segmentation network. Comput. Biol. Med. 150, 1–12 (2022)

2. Singh, V.K., Kalafi, E.Y., Wang, S., et al.: Prior wavelet knowledge for multi-modal medical image segmentation using a lightweight neural network with attention guided features. Expert Syst. Appl. 209, 1–13 (2022)

3. Wan, J., Yue, S., Ma, J., et al.: A coarse-to-fine full attention guided capsule network for medical image segmentation. Biomed. Signal Process. Control 76, 1–11 (2022)

4. Khehra, B.S., Singh, A., Kaur, L.M.: Masi entropy and grey wolf optimizer based multilevel thresholding approach for image segmentation. J. Inst. Eng. (India): Ser. B 103(5), 1619–1642 (2022)

5. Elaziz, M.A., Bhattacharyya, S., Lu, S.: Swarm selection method for multilevel thresholding image segmentation. Expert Syst. Appl. 138, 1–24 (2019)

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