In order to achieve geographical agreement in digital pathology, this research presents an aggregate computational architecture. The proposed Base-Comet-Infero architecture portrays histopathological specific patches as communicating computational nodes, building on ideas from FScaFi, MacroSwarm, and Exchange Calculus. Intercellular signaling and aggregate tissue function are simulated through the repeated exchange and stabilization of local evidence into coherent diagnostic fields. The technique guarantees scalable, topology-aware inference over whole-slide pictures of colorectal and cervical tissues. The results show that physiologically inspired field convergence improves interpretability, decreases diagnostic uncertainty, and increases spatial coherence. For next-generation explainable pathology systems, the paper creates a formal link between biomedical image analysis and distributed computing.