Intuitionistic Fuzzy Nano Topology Framework for Enhanced Medical Image Analysis and Cancer Diagnosis
Keywords:
Intuitionistic Fuzzy Sets, Nano Topology, Medical Image Processing, Cancer Diagnosis uncertainty Quantification, Computational Topology, Machine LearningAbstract
Cancer diagnosis via medical imaging is hindered by uncertainties, noise, and indistinct tissue boundaries. This paper presents a novel diagnostic framework integrating Intuitionistic Fuzzy Nano Topology (IFNT) with advanced digital image processing. By combining the triadic uncertainty modeling of intuitionistic fuzzy sets (membership, non-membership, hesitation) with the fine-grained precision of nano topology, the proposed system offers a mathematically rigorous approach. We introduce IFNT-based operators for adaptive edge detection, uncertainty-aware segmentation, and confidence-weighted classification, supported by convergence proofs, optimality conditions, and boundary characterization theorems.
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