This paper aims to make a review on the current segmentation algorithms used for medical images. Algorithms are classified according to their principal methodologies, namely the ones based on thresholds, the ones based on clustering techniques and the ones based on deformable models. The last type is focused on due to the intensive investigations into the deformable models that have been done in the last few decades. Typical algorithms of each type are discussed and the main ideas, application fields, advantages and disadvantages of each type are summarised. Experiments that apply these algorithms to segment the organs and tissues of the female pelvic cavity are presented to further illustrate their distinct characteristics. In the end, the main guidelines that should be considered for designing the segmentation algorithms of the pelvic cavity are proposed.

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A review of algorithms for medical image segmentation and their applications to the female pelvic cavity

With the growing interest to use composite materials and honeycomb sandwich panels in industrial fields, much attention is devoted to the development of non-destructive testing (NDT) techniques for the detection and evaluation of defects. In this work, scanning pulsed eddy current (PEC) was investigated and two features, representing the magnetic field intensity and conductivity, were used to characterise the different types of defects in carbon fibre reinforced plastics (CFRP) laminates and honeycomb sandwich panels. The experimental results show that the low energy impact from 4 J to 12 J, conductive and non-conductive insert defects can be effectively detected and evaluated using the proposed methods. The effectiveness was verified and the advantages of scanning PEC were addressed through comparative studies with flash thermography and shearography.

/pdf/non-destructive-testing-of-low-energy-impact-in-cfrp-49tfuzgv4p.pdf

Non-destructive testing of low-energy impact in CFRP laminates and interior defects in honeycomb sandwich using scanning pulsed eddy current

The moment segmentation analysis of heart sound pattern

Magnetic dipole localization methods have a wide application range. Resolving equations of magnetic gradient tensor is a classical method to obtain the direction of the relative position vector, but the real solution hides in four possible solutions. The Scalar Triangulation and Ranging (STAR) method is also effective but is less accurate than the real solution of tensor equations. To solve the two problems, we proposed a novel direction determination approach by combining the advantages of the two methods. Based on the cube tensor measurement array from the STAR method, a novel way to calculate the distance between the dipole and the sensor array is proposed. Then, a novel real-time magnetic dipole localization method is obtained. Results of simulation experiments indicate that our method raises the successful localization area by 43% compared with the traditional method, and the baseline length of the sensor array dominates the performance of our method.

A Real-Time Magnetic Dipole Localization Method Based on Cube Magnetometer Array

A correct riding posture is essential for a good performance in equestrian. This paper proposes a method of equestrian analysis based on body sensor networks. First of all, raw sensor data corresponding to professional (PRO) riders and beginners (BEGs) under different horse gaits were collected by inertial sensor nodes. Then, after an initial sensor alignment with the reduced error, a kind of motion reconstruction method based on the gradient descent method was used to fuse the sensor data to constantly update the rider’s attitude information. In addition, to evaluate the tracking accuracy of joint angle, an Northern Digital optical system was deployed to verify the accuracy of our method. Using the attitude information, the motions of riders in equestrian sports were reconstructed by combining the method of human kinematics. Finally, in view of the two aspects of exercise intensity and joint angle, a quantitative analysis of key features between PRO and BEG in walking and rising trot was carried out by combining with the kinematic analysis method. Experiments conducted in this paper demonstrate that the estimation errors are well controlled, and our method can better reflect the similarities and differences between PRO and BEG in equestrian sports and provide quantitative data for equestrian coaches or riders, which can be used to improve the riding skills of riders.

Inertial Sensor-Based Analysis of Equestrian Sports Between Beginner and Professional Riders Under Different Horse Gaits

Calibration of three-axis fluxgate magnetometers with nonlinear least square method

The magnetometer array is effective for magnetic object detection and localization. Calibration is important to improve the accuracy of the magnetometer array. A magnetic sensor array built with four three-axis DM-050 fluxgate magnetometers is designed, which is connected by a cross aluminum frame. In order to improve the accuracy of the magnetometer array, a calibration process is presented. The calibration process includes magnetometer calibration, coordinate transformation and misalignment calibration. The calibration system consists of a magnetic sensor array, a GSM-19T proton magnetometer, a two-dimensional nonmagnetic rotation platform, a 12 V-dc portable power device and two portable computers. After magnetometer calibration, the RMS error has been decreased from an original value of 125.559 nT to a final value of 1.711 nT (a factor of 74). After alignment, the RMS error of misalignment has been decreased from 1322.3 to 6.0 nT (a factor of 220). Then, the calibrated array deployed on the nonmagnetic rotation platform is used for ferromagnetic object localization. Experimental results show that the estimated errors of X, Y and Z axes are −0.049 m, 0.008 m and 0.025 m, respectively. Thus, the magnetometer array is effective for magnetic object detection and localization in three dimensions.

http://iopscience.iop.org/article/10.1088/0957-0233/24/7/075102/pdf

Calibration of a fluxgate magnetometer array and its application in magnetic object localization

Calibration of three-axis magnetometers with differential evolution algorithm

Nonlinearity is a prominent limitation to the calibration performance of vector magnetometers. A new calibration model is proposed to suppress the nonlinearity of magnetometers and improve calibration performance, in which the nonlinearity coefficients of scale factors are considered. The experimental system mainly consists of a three-axis fluxgate magnetometer (MAG3300), a 2D nonmagnetic rotation equipment, and a proton magnetometer (CZM-3), in which the nonmagnetic rotation equipment is used to change the position of three-axis fluxgate magnetometer, and the scalar value of magnetic field is obtained with the proton magnetometer and considered to be the true value. The principle of this new calibration method is analyzed, and the calibration procedures are introduced. Experimental results show that after nonlinearity suppression, the root-mean-square error of calibration can be reduced by three times. It suggests an effective way to improve the calibration performance of three-axis magnetometers.

A New Calibration Method of Three Axis Magnetometer With Nonlinearity Suppression

Fluxgate magnetometers are widely used for magnetic field measurement. However, their accuracy is influenced by temperature. In this paper, a new method was proposed to compensate the temperature drift of fluxgate magnetometers, in which a least-squares support vector machine (LSSVM) is utilized. The compensation performance was analyzed by simulation, which shows that the LSSVM has better performance and less training time than backpropagation and radical basis function neural networks. The temperature characteristics of a DM fluxgate magnetometer were measured with a temperature experiment box. Forty-five measured data under different magnetic fields and temperatures were obtained and divided into 36 training data and nine test data. The training data were used to obtain the parameters of the LSSVM model, and the compensation performance of the LSSVM model was verified by the test data. Experimental results show that the temperature drift of magnetometer is reduced from 109.3 to 3.3 nT after compensation, which suggests that this compensation method is effective for the accuracy improvement of fluxgate magnetometers.

http://iopscience.iop.org/article/10.1088/0957-0233/23/2/025008/pdf

Shitu Luo

Papers

Calibration of three-axis fluxgate magnetometers with nonlinear least square method

Calibration of a fluxgate magnetometer array and its application in magnetic object localization

Calibration of three-axis magnetometers with differential evolution algorithm

A New Calibration Method of Three Axis Magnetometer With Nonlinearity Suppression

Nonlinear temperature compensation of fluxgate magnetometers with a least-squares support vector machine