Resting-state (rs) fMRI has been shown its potential for pre-surgical mapping. Seed-correlation analysis is a commonly used approach for network detection. However, lesion-related spatial distortions and functional reorganization make the seed selection difficult for rs-fMRI mapping based on anatomical landmark alone. Here we proposed a novel approach to guide the seed selection for rs-fMRI mapping in patients with brain tumors by incorporating regional homogeneity (RH) confined by results of meta-analysis (MA). Our results showed performance that was equivalent to the seed localization guided by task-fMRI activation, suggesting the potential of RH+MA approach for rs-fMRI mapping in the clinical practice.