When examining relative cerebral blood volume (rCBV) between mice, values from the unwanted large vessels should be excluded, otherwise, they may result in findings that are not associated with the basal metabolism mapped by microvascular blood volume. Our proposed method provides an automated and robust approach to estimate the rCBV distribution in large vessels with the maximum likelihood estimation using expectation-maximization Gaussian mixture model and to help filter out this unwanted confounding. In research related to rCBV analysis, we suggest applying this as one preprocessing step, which may help improve both sensitivity and specificity when comparing rCBV between subjects.
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