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This paper outlines an algorithm to improve the robustness of missing data treatment to pathological motion (PM). PM can cause misdiagnosis of clean image data as missing data. The proposed algorithm uses a probabilistic framework to jointly detect PM and missing data by exploiting more temporal information than is typically used for missing data detection and by exploiting the local smoothness assumption of motion fields. The results of the framework are compared to an equivalent missing data detector without PM detection and the framework is shown to prevent the misdiagnosis of missing data due to PM.