Automatic grading of placental maturity based on LIOP and fisher vector

Currently, the evaluation of placental maturity has mainly focused on subjective measure, which highly depends on the observation and experiences of the clinicians and not reliable. This paper proposes a new method for grading placenta maturity in B-mod ultrasound (US) images automatically based on local intensity order pattern (LIOP) and fisher vector (FV). After extracting invariant LIOP feature from the affine covariant region, the feature is encoded by FV to improve the classification accuracy and reduce the processing time. Experimental results show the effectiveness of the proposed method with an accuracy of 0.9375, a sensitivity of 0.9804 and a specificity of 0.9375 for the placental maturity grading. Moreover, experimental results demonstrate that the LIOP feature outperforms the traditional SIFT feature for grading.