Cesarean Scar Syndrome (CSS) poses significant challenges in gynecology, notably affecting uterine peristalsis and potentially influencing fertility. This study introduces a novel feature extraction method from Cine MRI data to explore these issues. By employing the Time Series Feature Extraction Library (TSFEL) and Demon Registration for precise image alignment, our approach facilitates a comprehensive analysis of spectral, statistical, and temporal features from cine MRI scans. This study employed 20 patients who were categorized into groups according to the presence of CSS and further differentiated into pre-surgery and post-surgery cohorts. Our findings reveal significant spectral differences between these groups. This research highlights the potential of feature extraction techniques in improving the understanding and management of CSS's impact on fertility.