The existing imaging enhancement examination process faces issues such as suboptimal contrast agent injection schemes, lack of intelligent control over injectors, and disconnected operation steps, this paper proposed a Java-based integrated intelligent recommendation and control system for injection schemes to address these problems. Through the intelligent injection scheme recommendation, it established a model for recommending optimal injection schemes to realize the automatic recommendation of the most suitable injection scheme, thereby improving the effectiveness and safety of injections. Additionally, by integrating the injection equipment with image processing algorithms, the system achieved automated control over the injection scheme, thereby enhancing accuracy and consistency during injections. Furthermore, by monitoring the image data and physiological parameters during the injection process in real time, the system integrated the existing examination process, saved and displayed the process data to improve treatment effectiveness and enhance the patient experience. Ultimately, through the coordinated application of rules, case-based reasoning and deep neural networks, the system achieved intelligent generation of contrast agent schemes. And it also realized feedback and control over the high-pressure injector through a persistent connection, which provided a good comprehensive solution to improve the intelligence level of imaging enhancement, enhance the quality of medical processes and outcomes, and facilitate mutual recognition of medical results. The system has been successfully applied at West China Hospital, which can simplify operations in imaging enhancement examinations, improve image quality, reduce patient harm and medical resource waste.