Method for identifying, locating and tracking calibrating conduit within 3D ultrasound point cloud

A method for identifying, localizing and tracking a calibrating conduit within a three-dimensional (3D) ultrasound point cloud, comprising the following steps:

• Step S01:
• modeling an interior of a target environment;
• Step S02:
• performing human-computer interaction to locate a conduit in a user operation interface, and placing the conduit into a scannable range of an ultrasound probe;
• Step S03:
• after starting tracking and placing the conduit into the scannable range of the probe, performing, by the user, human-computer interaction operation on a display interface to frame an area where the conduit is located, and giving content in the frame a color to distinguish therefrom;
• making, by the user, a determination whether a conduit position is accurate, and if the framing is not correct, the user frames again until the conduit position is accurately identified;
• Step S04:
• after the conduit position is accurately identified, obtaining a range for positioning the conduit, and identifying and tracking the conduit;
• Step S05:
• identifying and obtaining a point cloud of the conduit, and taking the obtained point cloud as an input to obtain a field point cloud generated from a two-dimensional (2D) ultrasound image by a method for tracking a particle filter tracker;
• and
• Step S06:
• transmitting new conduit modeling information with the method for tracking the conduit, refreshing a display on a user interface, accurately coloring the conduit with a standard color, and changing a framed color as a standard conduit color and a background color accordingly;
• wherein in Step S05, a specific method for identifying the point cloud of the conduit is as follows:
• Step S51, in an initialization step, downsampling a framed point cloud to reduce an amount of data;
• Step S52:
• extracting a Scale Invariant Feature Transform (SIFT) key point of the point cloud;
• Step S53:
• then calculating Signature of Histogram of Orientation (SHOT) features for the SIFT key points, establishing a local coordinate system at the feature points, and combining spatial location information of neighboring points with geometric feature statistical information to describe the feature points;
• and
• Step S54:
• extracting the features, generating a feature vector, and inputting the feature vector into a support vector machine (SVM) classifier to obtain the point cloud of the conduit.