The Pseudo-color Mapping Model of Spect Reconstruction Data Based on Adjustable Dual-vector Parameters

SPECT performs imaging on the γ-ray emitted by radioactive particles implanted in the patient's body. The gray information of SPECT image represents counts of γ-ray, which can correspond to the radiation dose value of γ-ray after transformation. In order to observe the dose distribution near the lesion clinically, it is necessary to perform pseudo-color processing on SPECT images, which are then fused with CT images. However, the SPECT/CT pseudo-color processing of conventional processing software is difficult to provide sufficient dose detail resolution, which cannot meet the needs of clinical diagnosis and treatment. For the requirement of γ radiation dose distribution details in the treatment of brain tumors, we present a pseudo-color mapping model with adjustable dual-vector parameters, which is based on DICOM data of SPECT imaging and can bulid a multi-level mapping relationship.The proposed method can not only control the pseudo-color display area, but also adjust the multi-segment details of the dose display. Results of numerical experiments by Python show that the proposed mapping method can display the dose area and data range of interest in SPECT images more clearly and accurately. After being fused with the CT image, they can significantly enhance the layering of dose distribution in the SPECT/CT focus area,, and accurately display the information of particle space and radiation dose distribution. The proposed method can provide a reliable basis for the judgment of clinical efficacy.