Characterization of ultrasonic images of the placenta based on textural features

The assessment of the placenta maturity is an important issue in prenatal diagnosis. In this work, the task of classifying ultrasonic images of the placenta according with the gradation proposed by Grannum is attempted. With this purpose, the ability of a decision tree classifier to discriminate different textures with three sets of textural features was tested. The performance of the classifier using textural features corresponding to co-ocurrence matrices, Law's operators and neighborhood gray-tone difference matrices (NGDTM) was firstly assessed. A preliminary experiment was done using natural textures taken from Brodatz's album with the addition of an ultrasonic image of the placenta. In a second step the method was applied to the problem of the classification of ultrasonic images of the placenta corresponding to different grades.