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Contractions of the myocardium, respiratory excursions, peristalsis, vascular pulsatility, and unpredictable bulk patient movement generate artifacts that impair image quality, limit reproducibility, and may necessitate repeat scans. This review summarizes motion correction strategies in cardiac and abdominal MRI, emphasizing both clinical applications and methodological principles. Techniques to address motion can be broadly categorized into prospective and retrospective approaches. Prospective methods adjust acquisition in real time, for example through respiratory or cardiac gating, navigator echoes, or external sensors, while retrospective strategies apply corrections during or after reconstruction, using k\u2010space binning, image registration, or model\u2010based reconstructions. Rigid motion, such as translations or rotations of organs, can often be corrected efficiently, whereas non\u2010rigid motion including myocardial contraction or peristalsis requires more sophisticated elastic registration or motion\u2010compensated reconstruction. Application\u2010specific challenges and solutions are highlighted across cardiac cine imaging, flow quantification, tagging, and quantitative mapping, as well as abdominal imaging of the liver, kidneys, and gastrointestinal tract. In each domain, examples are provided of how motion impacts diagnostic performance and how motion correction strategies can mitigate these effects. Strengths and limitations of current approaches are reviewed, from conventional breath\u2010holding to advanced free\u2010breathing motion\u2010resolved imaging. Emerging trends include integration of artificial intelligence with motion\u2010compensated reconstruction, advanced sensor technologies for real\u2010time tracking, and hybrid approaches combining multiple strategies. While many methods remain research\u2010focused, vendor\u2010embedded solutions and open\u2010source tools are increasingly available, narrowing the gap between technical advances and routine practice. Motion correction is poised to become a core feature of clinical MRI, enabling faster, more robust, and patient\u2010friendly examinations that reduce repeat rates, improve diagnostic confidence, and expand access to high\u2010quality imaging in challenging patient populations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Evidence Level<\/jats:title>\n                    <jats:p>N\/A.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Technical Efficacy<\/jats:title>\n                    <jats:p>Stage 5.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jmri.70209","type":"journal-article","created":{"date-parts":[[2025,12,28]],"date-time":"2025-12-28T20:30:36Z","timestamp":1766953836000},"page":"917-937","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Motion Mitigation Techniques for Abdominal 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