With the access to the Internet and artificial intelligence, many medical fields have become more efficient and reliable. Modern anesthesiology extends beyond the operating room to include outpatient settings, endoscopy units, and more, placing an additional burden on anesthesiologists. The integration of radiology and anesthesiology provides more accurate, safe, and efficient methods for anesthesia procedures. The rapid development of deep learning technology brings cutting-edge innovations to this field. This paper summarizes the recent research findings related to deep learning in this interdisciplinary field, and categorizes and summarizes the relevant applications. Through literature analysis, we will focus on discussing specific applications such as image recognition and object positioning in the field of medical imaging. Finally, we explore the limitations and future directions of deep learning methods in the field of anesthesiology.