Multimodal Image Transformation And Efficacy Prediction For Esophageal Squamous Cell Carcinoma Radiotherapy

Esophageal squamous cell carcinoma(ESCC)is one of the malignant tumors with high morbidity and high mortality around the world.The morbidity and mortality of esophageal squamous cell carcinoma in China are very high,ranking among the top in the world.Esophageal squamous cell carcinoma can be resected in time,the treatment process is simple and effective.However,lacking of attention in the early stage,the majority of patients are in the middle and late stage.Therefore radiotherapy has become one of the main means.Due to the physical differences of different patients,the therapeutic effect after radiotherapy will be different.Some people will obviously improve after radiotherapy,while some people will not achieve the desired therapeutic effect.Therefore,patients and doctor are very concerned about the effect of radiotherapy,and it is of great significance to predict the effect of radiotherapy.In addition,the diagnosis of esophageal squamous cell carcinoma and the establishment and implementation of radiotherapy plan need image support,while CT image and PET image play an important role.Through the image analysis,we can extract a lot of effective information,which plays an important role in the diagnosis of patients' condition and the prediction of radiotherapy effect.With the current development of the computer industry and the rise of artificial intelligence,research in the medical field has been promoted and the dawn of work in the medical field has been brought forward.Patients with esophageal squamous cell carcinoma are also among the beneficiaries.In order to get more treatment opportunities for esophageal squamous cell carcinoma patients and predict the effect of radiotherapy in advance before radiotherapy,facilitate the diagnosis of the disease,the formulation of radiotherapy scheme,the evaluation of radiotherapy effect and solve the problem of the difference of treatment effect of different esophageal squamous cell carcinoma patients after radiotherapy,PET image can play an important role in the diagnosis,formulation of radiotherapy scheme,evaluation of radiotherapy effect,etc,Therefore,PET image generation is the first step in this study.At the same time,in order to solve the problem that individual differences of esophageal squamous cell carcinoma patients have different effects on radiotherapy,intelligent methods are used to predict the radiotherapy effect of esophageal squamous cell carcinoma,and an auxiliary radiotherapy platform for esophageal squamous cell carcinoma was built.In this way,it not only avoids repeated experiments on real patients,saves costs,but also reduces time,and provides certain auxiliary information for patients' future treatment.The main research contents of this article are as follows:(1)Transformation of multimodal imageCompared with ordinary CT images,PET images can reflect the activity information of esophageal squamous cell carcinoma.In order to achieve the required PET images at low cost,this research focuses on the development of CT image and PET image conversion technology for patients with esophageal squamous cell carcinoma.The conditional generation adversarial network was adopted to learn the mapping relationship between CT images of ESCC patients and their corresponding PET images.Experiments prove that through continuous iterative optimization,the model can generate realistic PET images corresponding to them from CT images,seeing from the results saved during the training process.(2)Prediction of radiotherapy effect of esophageal squamous cell carcinomaBecause different esophageal squamous cell carcinoma patients have different sensitivities to radiation therapy,being able to predict the effect of patients after radiation therapy in advance will be of great significance for patients' future treatment.In this study,the patient's CT image was used,and the gross tumor volume after radiation therapy was used as a prediction target.The three-dimensional convolutional neural network was used to predict the effect of radiotherapy on patients.The final experiment proved that the gross tumor volume predicted by the model was consistent with the actual value.(3)Adjuvant radiotherapy platform for esophageal squamous cell carcinomaBased on the obtained esophageal squamous cell carcinoma data conversion technology and radiotherapy effect prediction technology,this paper builds an esophageal squamous cell carcinoma auxiliary radiotherapy platform based on the framework of Spring,SpringMVC,MyBatis and the design concept of MVC system.The platform mainly realizes the modal image conversion function module and the function of predicting the efficacy of radiotherapy for esophageal squamous cell carcinoma.