In order to realize the rapid detection and classification of medical data, the surface reconstruction design of medical data needs to be carried out. A surface reconstruction algorithm of medical data based on improved total convolution neural network is proposed. The big data sampling of medical data was carried out by using radio frequency identification technology, the medical data collected by RFID was processed by information fusion, and the correlation statistical characteristics of medical data were extracted by multiple regression analysis. According to the characteristics of medical data, matching filter detector is used for redundant filtering, and phase space reconstruction technology is used to reconstruct medical data after purification. In order to realize the surface reconstruction and automatic recognition of medical data, an improved total convolution neural network classifier is used to classify and recognize the reconstructed data. The simulation results show that the proposed method has a good effect on the redundant feature processing of medical data. The accuracy of data classification is more than 90%, and the error of medical data reconstruction is smaller and the time consuming is less.