Empowered chaotic local search-based differential evolution algorithm with entropy-based hybrid objective function for brain tumor segmentation
Yükleniyor...
Tarih
Kasım, 2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/embargoedAccess
Özet
In neuro-oncology, the precise segmentation of brain tumors from Magnetic Resonance Images is crucial for diagnosis, treatment planning, and monitoring disease progression. Accurate segmentation helps determine the tumor’s size, location, and growth potential, which is essential for formulating effective treatment strategies. In response to this challenge, we developed a novel approach using Chaotic Local Search-Enhanced Differential Evolution (CJADE). CJADE, particularly its variant CJADE-M, which employs chaotic maps selected through a probability-based approach, has proven effective in optimizing brain tumor segmentation. Our study shows that CJADE-M outperforms traditional metaheuristic algorithms on various evaluation metrics. We further enhanced CJADE-M with an entropy-based hybrid objective function, which improved accuracy and reduced computational time in tumor segmentation compared to conventional methods like Minimum Cross-Entropy and Kapur. This makes our method suitable for real-time medical imaging analysis. Our findings indicate that CJADE-M, equipped with the hybrid objective function, achieves superior segmentation performance for both benign lobulated and malignant irregular tumors across metrics such as PSNR, FSIM, QILV, and HPSI. By providing a more accurate and efficient tool, our approach can significantly enhance the outcomes of brain tumor diagnosis and treatment, improving patient care in neuro-oncology.
Açıklama
Anahtar Kelimeler
Differential evolution, Hybrid objective function, Brain tumor segmentation, Metaheuristic optimization, Chaotic maps
Kaynak
Biomedical Signal Processing and Control
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
96
Sayı
Part A
Künye
Aydemir, S. B., Onay, F. K., & Yalcin, E. (2024). Empowered chaotic local search-based differential evolution algorithm with entropy-based hybrid objective function for brain tumor segmentation. Biomedical Signal Processing and Control, 96, 106631.
