Many research questions in dysphagia research require frame-by-frame annotation of anatomical landmarks visible in videofluorographs as part of the research workflow, which can be a tedious and error prone process. Such annotation is done manually using image analysis tools, is error prone, and characterized by poor rater reliability. In this thesis, a computer-assisted workflow that uses a point tracking technique based on the Kanade-Lucas-Tomasi tracker to semi-automate the annotation process, is developed and evaluated. Techniques to semi-automate the annotation process have been explored but none have had their research value demonstrated. To demonstrate the research value of a workflow based on point tracking in enhancing the annotation process, the developed workflow was used to perform an enhanced version of the recently published Coordinate Mapping swallowing study annotation technique to determine several swallowing parameters. Evaluation was done on eight swallow studies obtained from a variety of clinical sources and showed that the workflow produced annotation results with clinically insignificant spatial errors. The workflow has the potential to significantly enhance research processes that require frame-by-frame annotation of anatomical landmarks in videofluorographs as part of their data preparation steps, by reducing the total time required to annotate clinical cases