A Compressed Sensing approach for shortening acquisition time in Magnetic Resonance guided Focused Ultrasound (MRgFUS) thermometry is presented. The approach is based on the recently developed Fast MRI by Exploiting a Reference scan (FASTMER) method. The suggested method embeds into the CS optimization problem a regularization term related to a-priori knowledge about the similarity between pre-heating and post-heating acquired data. The results obtained from an in-vitro Focused Ultrasound (FUS) experiment demonstrate that the proposed method provides efficient and accurate temperature mapping from substantially subsampled k-space data. The method is suitable for data acquired with flexible undersampling schemes.