This review paper aims to guide researchers in effectively implementing language models in medical imaging research. It begins by presenting the fundamental principles and evolution of language models, with a focus on large language models. The paper then reviews current literature on how language models are improving medical imaging, covering applications such as image captioning, report generation, report classification, findings extraction, visual question response systems, and interpretable diagnosis. Notably, the capabilities of ChatGPT are highlighted for further exploration. The paper also discusses the advantages of accurate and efficient language models in enhancing clinical workflow efficiency, reducing diagnostic errors, and assisting clinicians in providing timely and accurate diagnoses. Overall, the goal is to inspire new ideas and innovations in integrating language models with medical imaging. The review concludes with a thorough analysis of the current research landscape and a forward-looking discussion on potential future directions.This review paper aims to guide researchers in effectively implementing language models in medical imaging research. It begins by presenting the fundamental principles and evolution of language models, with a focus on large language models. The paper then reviews current literature on how language models are improving medical imaging, covering applications such as image captioning, report generation, report classification, findings extraction, visual question response systems, and interpretable diagnosis. Notably, the capabilities of ChatGPT are highlighted for further exploration. The paper also discusses the advantages of accurate and efficient language models in enhancing clinical workflow efficiency, reducing diagnostic errors, and assisting clinicians in providing timely and accurate diagnoses. Overall, the goal is to inspire new ideas and innovations in integrating language models with medical imaging. The review concludes with a thorough analysis of the current research landscape and a forward-looking discussion on potential future directions.