An automatic approach for morphological analysis and malignancy evaluation of ovarian masses using B-scans.
Ovarian masses are a common phenomenon among women of all ages. The importance of prompt diagnosis of ovarian malignancies is obvious, due to the high mortality rate and the difficulty to detect a tumor in its early stages. In this work, an automatic technique for quantitative analysis and malignancy detection of ovarian masses using B-scan ultrasound (US) images is presented. The core of the technique is morphologic analysis of the ovarian mass. The method employed for this task is divided into two major stages: initial classification of the mass (into one of the three major tumor types: cyst, semisolid, solid), and detailed analysis of the mass. Malignancy evaluation is performed based on the collected data and the criteria provided by commonly used scoring systems. The results reflect adequate performance of the automatic method developed (referring to clinical requirements).
Zimmer
Yair
Y
Medical Physics Department, Tel Aviv University, Tel Aviv, Israel.
Tepper
Ron
R
Akselrod
Solange
S
D000465:Algorithms; D003937:Diagnosis, Differential; D005103:Expert Systems; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010048:Ovarian Cysts / Q000000981:diagnostic imaging; D010049:Ovarian Diseases / Q000000981:diagnostic imaging*; D010051:Ovarian Neoplasms / Q000000981:diagnostic imaging; D010053:Ovary / Q000000981:diagnostic imaging*; D012680:Sensitivity and Specificity; D014463:Ultrasonography