Research on Medical CT Image Data Analyses

This paper mainly analyzes the image data of multiple lesions. Analyses were conducted on the raw data such as the frequency statistics of lesions type, the distribution of lesion size, and the age distribution of patients. The analysis data mainly include lesion diameters pixel, coarse lesion type, patient age. Based on this foundation, silhouette coefficient and sum of the squared errors (SSE) are adopted to analysis the optimal K value for anchor boxes cluster. Through the analysis of medical image data, it can provide the foundation for predicting the growth of lesions. It can also be used to classify the lesions, and guide the development of general lesion detector based on database in the next work. This work can help doctors to make clinical diagnosis more comprehensively and improve the efficiency of clinical diagnosis.