Purpose: To test the reliability of two computational methods for segmenting cerebral iron deposits (IDs) in the aging brain, given that its measurement in magnetic resonance imaging (MRI) is challenging due to the similar effect produced by other minerals, especially calcium, on T2*-weighted sequences. Materials and Methods: T1-, T2*-weighted, and fluid-attenuated inversion recovery (FLAIR) MR brain images obtained at 1.5T from 70 subjects in their early 70s who displayed a wide range of brain IDs were analyzed. The first segmentation method used a multispectral approach based on the fusion of two or more structural sequences registered and mapped in the red/green color space followed by Minimum Variance Quantization. The second method employed a combined thresholding, size and shape analysis using T2*-weighted images augmented with visual information from T1-weighted data. Results: Both segmentation techniques had high intra- and interobserver agreement (95% confidence interval [CI] = +/- 57 voxels in a range from 0 to 1800), which decreased in subjects with significant microbleeds and/or IDs. However, the thresholding method was more observer dependent in identifying microbleeds and IDs boundaries than the multispectral approach. Conclusion: Both techniques proved to be in agreement and have good intra- and interobserver reliability. However, they have limitations, specifically with regard to automation and observer independence, so further work is required to develop fully user-independent methods of identifying cerebral IDs.