To solve the problem of automatic classification for ultrasound placenta images

we put forward an algorithm based on adaptive multiple neural networks. Two layers of BP net models were designed to carry Two-Stage separation of the placenta in this algorithm other than general one stage separation algorithm. When training networks

we do not adopt the common method which rounds the output of the networks

but propose a more reasonable grading rule

then present an adaptive threshold-gotten method to determine the reasonable placenta level. Experiments and clinic applications indicate that the similar classification result can be gotten by our algorithm as by experts

and the classification result by the algorithm before threshold division can give the doctor a good reference on the precise measurement of the placenta maturity

thereby

it has a good future in clinic applications.