The invention discloses a suspected micro-
calcification point region automatic positioning method based on a
discriminant deep belief network. The method comprises the following steps: 1)
mammary gland X-
ray image preprocessing: segmenting and enhancing a
mammary gland region; 2) sample acquisition and preprocessing: segmenting the enhanced
mammary gland image to obtain a sub-block image set for model training, and performing
noise reduction and background removal
processing on sub-blocks; 3) sub-block
feature extraction and classification: constructing a
discriminant deep belief network (DDBNs), training and finely adjusting a DDBNs model, and completing
feature extraction and automatic classification of mammary gland sub-blocks; and 4) micro-
calcification point
region detection: inputting a mammary gland X-
ray image to be detected, performing a series of preprocessing on the image, performing classification judgment on the sub-blocks by applying the trained optimal model, and markingsuspicious micro-
calcification point regions according to a judgment result. According to the method, automatic detection and positioning of the suspicious
lesion area can be completed, the
false positive rate is effectively reduced while the high
detection rate is obtained, and the detected calcification point area and the expert marking area have high consistency.