Ultrasound automated detection and display method of cranial abnormal regions
An ultrasound automated detection and display method of cranial abnormal regions includes: firstly, a skull surface model is constructed; then contour detection is carried out based on a two-dimensional ultrasonic image to obtain a skull contour curve; fitting is carried out on the contour curve and the skull surface model to determine whether the two-dimensional ultrasonic image has symmetry characteristics or not; finally, similarity comparison calculation is carried out on two mutually symmetrical regions by utilizing the symmetry characteristics of the two-dimensional image, so that whether an abnormal region exists and the location of the abnormal region is determined. The method has the advantages that a skull surface model is constructed before detecting a cranial contour curve on a two-dimensional ultrasonic image.
1 . An ultrasound automated detection and display method of cranial abnormal regions, comprising following steps:
S 01 , constructing a skull surface model using ultrasonic images obtained by performing ultrasonic scanning on a skull;
S 02 , performing cranial contour detection on the two-dimensional ultrasound images obtained by performing ultrasound scanning on the skull, and obtaining a cranial contour curve of the two-dimensional images;
S 03 , registering the cranial contour curve of the two-dimensional images obtained in step S 02 to the skull surface model obtained in step S 01 to determine the location of the two-dimensional images on the skull surface model;
S 04 , determining whether the two-dimensional images are symmetrical with respect to a median sagittal plane or a median coronal plane of the skull surface model according to the location of the two-dimensional images obtained in step S 03 on the skull surface model;
S 05 , marking the two-dimensional images which are symmetrical with respect to the median sagittal plane or median coronal plane of the skull surface model in step S 04 , and selecting two-dimensional images from them for analysis according to analysis requirements;
S 06 , dividing the two-dimensional images into two symmetrical regions, performing histogram statistics or grayscale co-occurrence matrix calculation on images of the two regions to obtain statistical data, performing normalization processing on the statistical data of the two regions to extract feature data, and then performing similarity comparison calculation on the feature data of the two regions when analyzing the two-dimensional images; and
S 07 , determining whether there is any difference between the two regions according to the calculated similarity, extracting the grayscale value at the point of the difference if there is a difference, segmenting and marking the abnormal region with the grayscale value as a guide and displaying such abnormal region.
2 . The ultrasound automated detection and display method of cranial abnormal regions according to claim 1 , wherein when contour detection is performed on the two-dimensional image in step S 02 , the contour between the skull and the cranial tissues is detected by using the grayscale or grayscale plus grayscale gradient value, and the contour is filtered and fitted to obtain the skull contour curve.
3 . The ultrasound automated detection and display method of cranial abnormal regions according to claim 1 , wherein when the skull surface model is constructed in step S 01 , three-dimensional ultrasound image scanning is performed on the brain; boundary detection on the three-dimensional ultrasound images between the skull and the cranial tissues is detected by using the grayscale or grayscale plus grayscale gradient value, and the boundary is filtered and fitted to obtain the skull surface model.
4 . The ultrasound automated detection and display method of cranial abnormal regions according to claim 1 , wherein when the skull surface model is constructed in step S 01 , two-dimensional ultrasound image scanning is performed on the brain; contour detection on the two-dimensional ultrasound image between the skull and the cranial tissues is detected by using the grayscale or grayscale plus grayscale gradient value, and the contours by using multiple two-dimensional ultrasonic images are filtered and fitted to obtain the skull surface model.