Automatic motion analysis system for pyloric flow in ultrasonic videos.

Ultrasonography has been widely used to evaluate duodenogastric reflux (DGR). But to the best of our knowledge, no automatic analysis system was developed to realize the quantitative computer-aided analysis. In this paper, we propose a system to perform the automatic detection of DGR in the ultrasonic image sequences by applying the automatic motion analysis. The motion field is estimated based on image velocimetry. Then, an intelligent motion analysis is applied. For the DGR detection, the motion and structural information is combined to analyze the transploric motion of the fluid. In order to test the performance of the proposed system, we designed the experiment with the real and synthetic ultrasonic data. The proposed system achieved a good performance in the DGR detection. The automatic results were accordant with the gold standard in analyzing the fluid motion. The proposed system is supposed to be a promising tool for the study and evaluation of DGR.

Weighted cross-correlation based variational optical flow for gastric flow analysis in ultrasonic videos.

PURPOSE: Estimating the fluid motion in ultrasonic videos is a crucial step in the analysis of duodenogastric reflux. Severe image noise and illumination changes in the pyloric region (the region of interest) challenge the accurate estimation of gastric flow. In this paper, the authors propose an illumination-robust optical flow method based on the weighted cross-correlation. METHODS: Cross-correlation was combined with the variational optical method framework as an illumination-robust local feature identifier. In consideration of accuracy near edges, they constructed visual similarity weights according to the characteristics of ultrasonic images. A processing procedure containing coarse-to-fine step and refinement was designed to get the final results. They tested the proposed method on synthetic and real ultrasonic images and compared it with other three optical flow methods. For quantitative evaluation, two metrics of angular and amplitude error were used. RESULTS: The synthetic results demonstrate that the proposed method performs better on ultrasonic images, with angular error of 4.1° and amplitude error of 3.3%. In qualitative comparison, the proposed method kept the motion field smooth in the homogeneous region while preserving edge information. When they used the results of the proposed method to judge the gastric flow direction, the automatic judgments agreed well with visual observation. CONCLUSIONS: The proposed method is a good tool for image velocimetry in ultrasonic images. It provides promising results to estimate the motion of gastric flow in ultrasonic videos.

Tracking pylorus in ultrasonic image sequences with edge-based optical flow.

Tracking pylorus in ultrasonic image sequences is an important step in the analysis of duodenogastric reflux (DGR). We propose a joint prediction and segmentation method (JPS) which combines optical flow with active contour to track pylorus. The goal of the proposed method is to improve the pyloric tracking accuracy by taking account of not only the connection information among edge points but also the spatio-temporal information among consecutive frames. The proposed method is compared with other four tracking methods by using both synthetic and real ultrasonic image sequences. Several numerical indexes: Hausdorff distance (HD), average distance (AD), mean edge distance (MED), and edge curvature (EC) have been calculated to evaluate the performance of each method. JPS achieves the minimum distance metrics (HD, AD, and MED) and a smaller EC. The experimental results indicate that JPS gives a better tracking performance than others by the best agreement with the gold curves while keeping the smoothness of the result.