In magnetic resonance imaging (MRI), a patient is exposed to beat-like knocking sounds,\noften interrupted by periods of silence, which are caused by pulsing currents of the MRI scanner.\nIn order to increase the patient�s comfort, one strategy is to play back ambient music to induce positive\nemotions and to reduce stress during the MRI scanning process. To create an overall acceptable\nacoustic environment, one idea is to adapt the music to the locally periodic acoustic MRI noise.\nMotivated by this scenario, we consider in this paper the general problem of adapting a given\nmusic recording to fulfill certain temporal constraints. More concretely, the constraints are given\nby a reference time axis with specified time points (e.g., the time positions of the MRI scanner�s\nknocking sounds). Then, the goal is to temporally modify a suitable music recording such that its beat\npositions align with the specified time points. As one technical contribution, we model this alignment\ntask as an optimization problem with the objective to fulfill the constraints while avoiding strong\nlocal distortions in the music. Furthermore, we introduce an efficient algorithm based on dynamic\nprogramming for solving this task. Based on the computed alignment, we use existing time-scale\nmodification procedures for locally adapting the music recording. To illustrate the outcome of our\nprocedure, we discuss representative synthetic and real-world examples, which can be accessed via\nan interactive website. In particular, these examples indicate the potential of automated methods for\nnoise beautification within the MRI application scenario.
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