Adaptive soft erasure with edge self-attention for weakly supervised semantic segmentation: Thyroid ultrasound image case study

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Performance optimization of differential evolution with slime mould algorithm for multilevel breast cancer image segmentation

Lei Liu et al.

Summary: This paper introduces a modified differential evolution algorithm based on slime mould for breast cancer image segmentation, and demonstrates that the developed multilevel image segmentation model has good performance. Experimental results show that the method has high convergence accuracy and the ability to escape local optima.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

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Article Biology

Performance optimization of salp swarm algorithm for multi-threshold image segmentation: Comprehensive study of breast cancer microscopy

Songwei Zhao et al.

Summary: This paper presents a novel approach to improve the Salp Swarm Algorithm (SSA), named EHSSA, which is applied to Multi-threshold image segmentation (MIS). By enhancing the global search capability of the algorithm, it successfully avoids local optimal drawbacks and proves its effectiveness and performance through experiments.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

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Article Biology

Gaussian Barebone Salp Swarm Algorithm with Stochastic Fractal Search for medical image segmentation: A COVID-19 case study

Qian Zhang et al.

Summary: An effective segmentation method called GBSFSSSA based on non-local mean 2D histogram and 2D Kapur's entropy was designed by combining Gaussian Barebone and Stochastic Fractal Search mechanism, balancing global and local search abilities. The algorithm showed advantages in performance compared to other competitive algorithms in CEC2017 competition dataset and COVID-19 CT image segmentation, proving its reliability and effectiveness.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

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Article Computer Science, Information Systems