A Boundary Detection Algorithm for Ultrasonic Kidney Images

Renal volume is an important parameter in clinical settings both for the adult, newborns and fetuses. About the former, evaluation and follow-up of patients with urinary tract infections, renal vessels stenosis and others are done in terms of both the length and the volume within the organ. About newborns and fetuses, the neonatal hydroneohrosis is detected by means of abnormal large volumes enclosed by the organ. Therefore, the boundary detection problem of kidney is important for the doctors to diagnose pathology. But Solutions proposed so far in the literature are very application-driven so they do not constitute a complete and valid method when applied to the boundary detection problem of ultrasonic kidney images. This research is based on star algorithm, and matches the rationale of markov random fields to detect the boundary of ultrasonic kidney images. We hope to combine the advantages of star algorithm and markov random fields, and develop an algorithm with near automation and high speed for the purpose of the computer aided diagnosis.