Modeling of Hidden Markov in Ultrasound Image-Assisted Diagnosis

Different segmentation of lung nodules using the same algorithm can easily lead to excessive errors. Therefore, it is necessary design an effective improve image accuracy. Based on hidden Markov model, this study processed ultrasound images pulmonary their diagnostic results. At time, was combined with process images. In addition, combines convex hull for processing, uses improved vector method repair, improves recognizability, establishes a reliable feature extraction algorithm, and comprehensive model. Finally, designed test performance analysis. Through experimental research, be seen that model constructed in has certain clinical effects provide theoretical reference subsequent related research.