US 11,744,541 B2
Method for measuring parameters in ultrasonic image and ultrasonic imaging system
Huifang Wang, Shenzhen (CN); Yongquan Lai, Shenzhen (CN); Yaoxian Zou, Shenzhen (CN); Muqing Lin, Shenzhen (CN); and Zhijie Chen, Shenzhen (CN)
Assigned to Shenzhen Mindray Bio-Medical Electronics Co., Ltd., Shenzhen (CN); and Shenzhen Second People's Hospital, Shenzhen (CN)
Filed by SHENZHEN MINDRAY BIO-MEDICAL ELECTRONICS CO., LTD., Guangdong (CN); and SHENZHEN SECOND PEOPLE'S HOSPITAL, Guangdong (CN)
Filed on Dec. 7, 2021, as Appl. No. 17/544,330.
Application 17/544,330 is a continuation of application No. 16/478,094, previously published as PCT/CN2017/071277, filed on Jan. 16, 2017.
Prior Publication US 2022/0087637 A1, Mar. 24, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. A61B 8/08 (2006.01); A61B 5/00 (2006.01); A61B 8/00 (2006.01)
CPC A61B 8/085 (2013.01) [A61B 5/7267 (2013.01); A61B 8/463 (2013.01); A61B 8/467 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method for measuring a parameter in an ultrasound image, comprising:
obtaining a pelvic ultrasound image with an ultrasound probe, wherein the pelvic ultrasound image contains an area representing the pelvic floor tissue;
displaying, by an image processor, the pelvic ultrasound image on a display device;
automatically determining, by the image processor by using a pattern recognition model, a position of an inferoposterior margin of symphysis pubis in the pelvic ultrasound image;
automatically determining, by the image processor, a central axis of symphysis pubis in the pelvic ultrasound image;
automatically determining, by the image processor, a first axis that passes through the position of the inferoposterior margin of symphysis pubis and is at an angle of 135 degree with respect to the central axis of symphysis pubis;
automatically determining, by the image processor by using the pattern recognition model, a position of a bladder neck in the pelvic ultrasound image, wherein the pattern recognition model is obtained by training one of a ascade adaBoost detector using Haar features, a cascade adaBoost detector using Local Binary Patterns features, a support Vector Machine detector, or a detector based on neural network with positive image samples containing the inferoposterior margin of symphysis pubis and the bladder neck and negative image samples not containing the inferoposterior margin of symphysis pubis and the bladder neck; and
calculating a distance from the position of the bladder neck to the first axis to obtain a value of a bladder neck-symphyseal distance.