Haijiang Zhu

Segmentation of liver cyst in ultrasound image based on adaptive threshold algorithm and particle swarm optimization

To find the optimum threshold of an image is still an important research topic in the recent years. This paper presents a segmentation of liver cyst for ultrasound image through combining Wellner’s thresholding algorithm with particle swarm optimization (PSO). The proposed method firstly obtains an optimal parameter, which expressed as a percentage or fixed amount of dark objects against a white background in a gray image, of Wellner’s thresholding algorithm by PSO method. And then the gray image is binarized according to the optimized parameter. Finally, a semi-automatic method for locating and identifying multiple liver cysts or single liver cyst of ultrasound images is performed. For a validation, the results of the proposed technique are compared with those of other segmented methods. We also tested 92 ultrasound images of the liver cysts by our software. The corrected identification rate of the single liver cysts is 97.7xa0%, and that of multiple liver cysts is 87.5xa0%. Experimental results demonstrate that the proposed technique is reliable on segmenting the contour of liver cyst and identifying single or multiple liver cysts.

Improved maximally stable extremal regions based method for the segmentation of ultrasonic liver images

The goal of this paper is to propose a modified maximally stable extremal region (MSER) based method for the segmentation of ultrasound liver images. Firstly, the feature regions including liver lesions are extracted using the modified MSER detector. Unlike the MSER algorithm, the improved MSER detector merely needs dozens of gray levels rather than 256 possible gray levels ranging from 0 to 255. Next, the edges of the liver lesions are detected from the binary images, and a merging strategy is designed to refine the contour of the liver lesion. The last step is the segmentation of the liver lesion according to the refined contour. The segmentation results of ultrasound liver images demonstrate that there is a significant correlation between the liver lesions selected by a medical expert and the liver lesions segmented by the proposed method. A comparison of the proposed method and other segmented methods shows that the proposed method can detect a more accurate contour of liver lesion images.

Approximate model of fisheye camera based on the optical refraction

This paper proposes an approximate model of fisheye camera based on the optical refraction. The model of fisheye lens is firstly derived from the optical refraction and the structure of fisheye lenses. Secondly, a suitable linearization of the fisheye model is developed in order to obtain an approximate model, and the approximate model including two parameters is constructed from the linearization of the fisheye model. Finally, the estimation algorithm on the model parameters is presented using the epipolar constraint between two fisheye images. Furthermore, we provide lots of experiments with synthetic data and real fisheye images. To start with, the feasibility of the approximate model is tested through fitting the five common designed model of fisheye lens with synthetic data. Two groups of experiments with real fisheye image are then performed to estimate the model parameters. In practical situation, this method can automatically establish image correspondences using an improved random sample consensus algorithm without calibration objects.

Quality-relevant fault monitoring based on locally linear embedding enhanced partial least squares statistical models

The multivariate statistical process monitoring methods represented by the partial least squares method are widely used in quality control and fault diagnosis. However, the existing partial least squares method has certain shortcomings in application. In order to enhance the nonlinear processing ability of system monitoring, a locally linear embedding enhanced partial least squares (LLEEPLS) model is proposed to enhance the local retention ability. By integrating the advantages of partial least squares and local linear embedding, the LLEEPLS model not only has the capability of PLS to extract the maximum correlation information between process variables and quality variables, but also enhance the local retention ability of PLS to keep the local structural information of the sampling data. The simulation of S-curve three-dimensional data shows that the LLEEPLS model can keep the local and global features of the original data better. And the results of TEP simulation verify the performance of LLEEPLS method for the quality-related fault diagnosis is better than that of the existing PLS model.

Visualization and measurement of the acoustic field of the piston transducer

Purpose – This paper aims to characterize the acoustic field radiated by the piston transducer and measure a few parameters through the data visualization method.Design/methodology/approach – Using the theoretical model of the ultrasonic transducer, the acoustic field data were acquired by scanning the ultrasound field of the piston transducer. And the visualized graphs of the ultrasonic data were displayed through 3D graphs including slice, iso‐surface and volume rendering, respectively. Furthermore, a few parameters of the transducer including beam width and spread angle were measured using the visualized data.Findings – The visualized graphs of the acoustic field radiated by the piston transducer show that the data visualization method can expose obviously the space distribution of the ultrasound field and describe directly the cylindrical shape. And this method provides the basis of reliable measurement and assess for the ultrasonic transducer.Research limitations/implications – This paper presents a ...

Using vanishing points to estimate parameters of fisheye camera

This study presents an approach for estimating the fisheye camera parameters using three vanishing points corresponding to three sets of mutually orthogonal parallel lines in one single image. The authors first derive three constraint equations on the elements of the rotation matrix in proportion to the coordinates of the vanishing points. From these constraints, the rotation matrix is calculated under the assumption of the image centre known. The experimental results with synthetic images and real fisheye images validate this method. In contrast to the existing methods, the authors method needs less image information and does not know the three-dimensional reference point coordinates.

Improved graph-cut segmentation for ultrasound liver cyst image

An optimal contour segmentation for ultrasonic liver cyst image is presented through combining graph-based method with particle swarm optimization (PSO) in this paper. After automatic selecting the region of interest (ROI) for ultrasonic liver cyst image, our method developed firstly a kind of multiple classes merging scheme by jointing the graph-based segmented result with the intensity of original ultrasound image. Then the evaluation function in the PSO was modified to optimize the parameter. Finally, the liver cysts were segmented according to the optimized parameter. In the experiment, we tested the influence of weight value on the improved method. And five indicators, which included Hausdorff distance (HD), mean absolute distance (MD), true positive volume fraction (TPVF), false-negative volume fraction (FNVF) and false-positive volume fraction (FPVF), were estimated to verify the improved method. Experimental results have validated that the improved method may extract successfully and accurately the contour of liver cyst.

Three-Dimensional Reconstruction of Ultrasound Images Based on Area Iteration

Ultrasonic C scan technique has been extensively applied in nondestructive testing (NDT) in recent years. Aiming at ultrasonic C scanning original data, this paper presents a 3D reconstruction algorithm for ultrasonic C scanning image based on area iteration. Because the distance between two neighboring slices is small, the area chance between two neighboring images is also few. Therefore, we design an iterative rule on the area of the object to detect and extract the target contour of each image. After preprocessing of ultrasonic C image, we extract the contour of the object scanned by ultrasonic transducer. Then, we reconstruct the 3D ultrasonic C scanning image using marching cube algorithm. In experiments, we implement the proposed method for ultrasonic scanning data of tissue-mimicking phantom including a liver model, and we compare the proposed method with other methods. The results show that the proposed method can more accurately display the edge information of the scanned object, and improve the precision of region detection, especially suitable when the edge has the incomplete information.

Ultrasound images of gray contrast tissue-mimicking phantom

This paper prepared a tissue-mimicking ultrasound phantom to test the contrast of ultrasonic equipment and presented the analysis of ultrasound image based on support vector machine (SVM). The gray contrasts in the tissue-mimicking phantom are regulated by changing scatter particles aluminum and corn starch. Embedded at depths of 3, 5, 7, 9, 11, and 13cm were set of cylindrical inclusions, not including scatter particles, in the axial direction. Six cylinder inclusions, containing tissue-mimicking material with a different scatter size and number density, were set in the lateral direction. Attenuations and backscatter coefficients of the background and the cylinder targets are independently measured to verify the phantom. Images obtained while scanning the prepared phantom with ultrasound diagnostic systems are available to test the gray contrast of the phantom. Furthermore, the gray contrast between cylindrical inclusions and background material is estimated for ultrasound image. And the cylinder targets segmentation based on the SVM method is performed for ultrasonic image. The experimental result shows that the prepared phantom can be utilized to test ultrasound diagnostic systems.

Discussion on the absolute calibration of piezoelectric acoustic emission sensors

The calibration of acoustic emission sensor is important for acoustic emission quantitative evaluation. To carry out the sensor calibration, one way is to find a reference acoustic emission source, such as a falling solid ball, a fracturing pencil lead, with energy evaluation to obtain the characteristics of the reference source. One way is to use a reference sensor to measure the pressure or the normal velocity at the surface, including the capacitive transducer and the laser interferometer. The other is using reciprocity method. Frequency characteristics of amplitude of absolute sensitivity of both the Rayleigh and longitudinal waves could be determined by purely electrical measurement without the use of mechanical sound sources of reference transducers. In this paper, the progress of the methods of the AE sensor calibration was given. The principles and the merits and faults of each method are discussed. In this paper the rapid calibration method by pulse exciting transducer was also discussed in different wave mode, as well as Face to Face method.