Novel fungal growth optimizer with orthogonal learning improves lung CT segmentation

OLFGO, a new fungal growth optimizer with orthogonal learning, ranked first for lung CT segmentation in a 20-image test vs. existing methods (exact metrics not reported).

• Tested on 20 chest CT images from a public lung cancer database using multilevel thresholding (2–12 levels).
• OLFGO ranked first in Friedman test against other optimization and deep learning methods, but specific Dice, PSNR, or SSIM values are absent from the abstract.
• Limitations: very small sample (n=20), no external validation, retrospective single-dataset evaluation.

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