Novel Information-Driven Smoothing Spline Linearization Method for High-Precision Displacement Sensors Based on Information Criterions.

A noise-resistant linearization model that reveals the true nonlinearity of the sensor is essential for retrieving accurate physical displacement from the signals captured by sensing electronics. In this paper, we propose a novel information-driven smoothing spline linearization method, which innovatively integrates one new and three standard information criterions into a smoothing spline for the high-precision displacement sensors' linearization. Using theoretical analysis and Monte Carlo simulation, the proposed linearization method is demonstrated to outperform traditional polynomial and spline linearization methods for high-precision displacement sensors with a low noise to range ratio in the 10-5 level. Validation experiments were carried out on two different types of displacement sensors to benchmark the performance of the proposed method compared to the polynomial models and the the non-smoothing cubic spline. The results show that the proposed method with the new modified Akaike Information Criterion stands out compared to the other linearization methods and can improve the residual nonlinearity by over 50% compared to the standard polynomial model. After being linearized via the proposed method, the residual nonlinearities reach as low as ±0.0311% F.S. (Full Scale of Range), for the 1.5 mm range chromatic confocal displacement sensor, and ±0.0047% F.S., for the 100 mm range laser triangulation displacement sensor.

DeepHeartCT: A fully automatic artificial intelligence hybrid framework based on convolutional neural network and multi-atlas segmentation for multi-structure cardiac computed tomography angiography image segmentation.

Cardiac computed tomography angiography (CTA) is an emerging imaging modality for assessing coronary artery as well as various cardiovascular structures. Recently, deep learning (DL) methods have been successfully applied to many applications of medical image analysis including cardiac CTA structure segmentation. However, DL requires a large amounts of data and high-quality labels for training which can be burdensome to obtain due to its labor-intensive nature. In this study, we aim to develop a fully automatic artificial intelligence (AI) system, named DeepHeartCT, for accurate and rapid cardiac CTA segmentation based on DL. The proposed system was trained using a large clinical dataset with computer-generated labels to segment various cardiovascular structures including left and right ventricles (LV, RV), left and right atria (LA, RA), and LV myocardium (LVM). This new system was trained directly using high-quality computer labels generated from our previously developed multi-atlas based AI system. In addition, a reverse ranking strategy was proposed to assess the segmentation quality in the absence of manual reference labels. This strategy allowed the new framework to assemble optimal computer-generated labels from a large dataset for effective training of a deep convolutional neural network (CNN). A large clinical cardiac CTA studies (n = 1,064) were used to train and validate our framework. The trained model was then tested on another independent dataset with manual labels (n = 60). The Dice score, Hausdorff distance and mean surface distance were used to quantify the segmentation accuracy. The proposed DeepHeartCT framework yields a high median Dice score of 0.90 [interquartile range (IQR), 0.90-0.91], a low median Hausdorff distance of 7 mm (IQR, 4-15 mm) and a low mean surface distance of 0.80 mm (IQR, 0.57-1.29 mm) across all segmented structures. An additional experiment was conducted to evaluate the proposed DL-based AI framework trained with a small vs. large dataset. The results show our framework also performed well when trained on a small optimal training dataset (n = 110) with a significantly reduced training time. These results demonstrated that the proposed DeepHeartCT framework provides accurate and rapid cardiac CTA segmentation that can be readily generalized for handling large-scale medical imaging applications.

All-optical laser-ultrasonic technology for width and depth gauging of rectangular surface-breaking defects.

In this paper, the width and depth of rectangular surface-breaking defects were successfully gauged using an all-optical laser-ultrasonic system. The finite element method was used to simulate propagating paths of defect-induced reflected and transmitted Rayleigh waves. It is observed that most Rayleigh waves with wavelengths less than the depth of the defect are reflected by the defect. A small part of the Rayleigh waves with wavelengths greater than the depth of the defect directly transmits through the bottom edge of the defect without acting on the left edge of the defect. Based on the simulation results, a three-step detection method of width and depth gauging of rectangular surface-breaking defects is proposed. In the first step, the pulsed laser and detection laser are irradiated on one side of the defect. In the second step, the sample is moved to a certain distance to ensure that both lasers reach the other side of the defect. In the third step, two lasers are irradiated on both sides of the defect. The width and depth of the defect are calculated according to the arrival time of the incident, reflected, and transmitted Rayleigh waves, as well as the movement distance of the sample. Experimental results are consistent with the reference-results measured by using a digital microscope. The proposed three-step detection method is proved to be feasible in simultaneous measurement of the width and depth of rectangular surface-breaking defects. Furthermore, it may be potentially useful for measuring other types of defect structures.

A new method for detecting surface defects on curved reflective optics using normalized reflectivity.

Detection of surface defects is critical in quality control of reflective optics. In this note, we propose a new surface defect detection method for reflective optics using the normalized reflectivity, which is calculated from the signal intensity of a chromatic confocal surface profiler. This detection method first scans the surface to acquire signal intensity data and then models the intensity data to calculate the normalized local reflectivity map. The reflectivity map is further processed by threshold segmentation to extract defects from normal areas. Measurement experiments on an Al-coated concave reflector with artificial defects were carried out to demonstrate the feasibility of the method. This detection method can provide existing optical surface profilers with defect detecting capabilities without extra equipment.

3D printed multi-scale scaffolds with ultrafine fibers for providing excellent biocompatibility.

It is a dilemma that both strength and biocompatibility are requirements for an ideal scaffold in tissue engineering. The normal strategy is mixing or coating another material to improve the biocompatibility. Could we solve this dilemma by simply adjusting the scaffold structure? Here, a novel multi-scale scaffold was designed, in which thick fibers provide sufficient strength for mechanical support while the thin fibers provide a cell-favorable microenvironment to facilitate cell adhesion. Moreover, we developed a promising multi-scale direct writing system (MSDWS) for printing the multi-scale scaffolds. By switching the electrostatic field, scaffolds with fiber diameters from 3 µm to 600 µm were fabricated using one nozzle. Using this method, we proved that PCL scaffolds could also have excellent biocompatibility. BMSCs seeded on the scaffolds readily adhered to the thin fibers and maintained a high proliferation rate. Moreover, the cells bridged across the pores to form a cell sheet and gradually migrated to the thick fibers to cover the entire scaffold. We further combined the scaffolds with hydrogel for 3D cell culture and found that the fibers enhanced the strength and induced cell migration. We believe that the multi-scale scaffolds fabricated by an innovative 3D printing system have great potential for tissue engineering.

3D printing of complex GelMA-based scaffolds with nanoclay.

Photo-crosslinkable gelatin methacrylate (GelMA) has become an attractive ink in 3D printing due to its excellent biological performance. However, limited by low viscosity and long cross-linking time, it is still a challenge to directly print GelMA by extrusion-based 3D printing. Here, to balance the printability and biocompatibility, biomaterial ink composed of GelMA and nanoclay was specially designed. Using this ink, complex scaffolds with high shape fidelity can be easily printed based on the thixotropic property of nanoclay. In this study, we tried to answer some basic printing-required questions of this ink, including the printability window, general properties (porosity, mechanical strength, et al), and biocompatibility. We found that the GelMA/Nanoclay ink enabled printing complex 3D scaffolds, such as a bionic ear and a branched vessel. Furthermore, the addition of nanoclay improved the porosity, increased the mechanical strength, reduced the degradation ratio, and maintained a good biocompatibility of the printed scaffolds. Therefore, this method offers an easy way to print complex scaffolds with good shape fidelity and biological performance, and it might open up new potential applications for the customized therapy of tissue defects.

Simultaneous ultrasonic parameter estimation of a multi-layered material by the PSO-based least squares algorithm using the reflection spectrum.

Advanced multi-layered materials with superior performance are required for many applications. The non-destructive characterization of multi-layer properties is a hot spot of current research. The least squares inversion method using the reflection spectrum has been developed and widely used to estimate the properties of thin single layers simultaneously. However this method has the problems of a loss in speed and simplicity, and a local optimal solution, especially in the cases of a multi-layered structure because of the increasing estimated parameters and the uncertainty influence from the parameters. Particle swarm optimization (PSO) is a robust global search algorithm similar to 'bird' foraging, which can be used to improve the performance of the least squares inversion algorithm. This paper has proposed a PSO-based least squares estimation using the ultrasonic reflection spectrum to make simultaneous measurement. The simulation and experiment, carried out on the aluminum-TC4 bi-layered material, tested and proved the capability of the new algorithm. The real measured parameters and the estimated parameters were obtained. The results have been compared to analyze the errors of the estimated parameters.

A rotary scanning method to evaluate grooves and porosity for nerve guide conduits based on ultrasound microscopy.

Grooved nerve guide conduits (NGCs) have been effective in the clinical treatment of peripheral nerve injury. They are generally fabricated from a micro-structured spinneret using a spinning process, which easily can cause a variety of pores and morphological deviation. The topography of internal grooves as well as the porosity can greatly influence the therapeutic effect. Traditional optical or scanning electron microscopy (SEM) methods can be used to image the grooves; however, these methods are destructive and require slicing NGCs to prepare specimens suitable for imaging. Moreover, lengthy experiments and large batches of NGCs are required to ensure reliable results from both in vitro experiments and clinical studies. In this paper, a non-destructive method for evaluating the grooves and porosity of NGCs is proposed using ultrasonic imaging combined with rotary scanning and an image analysis algorithm. Two ultrasonic methods were used: a 25-MHz point-focus ultrasonic transducer applied to observe axial cross sections of the conduits and a 100-MHz point-focus ultrasonic transducer to detect large pores caused by defects. Furthermore, a theoretical algorithm for detecting the local porosity of a conduit based on density is proposed. Herein, the proposed acoustic method and traditional optical methods are evaluated and compared. A parameter representing the specific surface area of the internal grooves is introduced and computed for both the optical and acoustic methods, and the relative errors of the computed parameter values for three different NGCs were 7.0%, 7.9%, and 15.3%. The detected location and shape of pores were consistent between the acoustic and optical methods, and greater porosity was observed in the middle of the conduit wall. In this paper, the results of the acoustic and optical methods are presented and the errors relating to the acoustic factors, device characteristics, and image processing method are further analyzed.

Numerical and experimental analysis of a focused reflected wave in a multi-layered material based on a ray model.

A focal probe is used for the acoustic measurement of a thin layer of a material with unknown sound velocity. This is now possible, because an algorithm, based on the focused ray model, has been found. However, there are still several problems such as the assumption that the half-aperture angle equals the incident angle, the identification of the longitudinal-wave focus, and the composition of the signal. In this work, we study the multi-mode wave focus numerically and experimentally to identify the focused longitudinal waves. A theoretical multilayered focusing model has been introduced based on geometrical acoustics. In addition, a phase differentiation theory is proposed to find the incident angle for the focus of the tilted rays, which is referred to as maximum half-aperture angle in other studies. The V(z,t) curve of a single layer, with a thickness of 1.5 mm and 2.0 mm, and a multi-layer are obtained using vertical translational movement. Both thickness and sound velocity are derived from the curve simultaneously. Our single layer experiments show that it is possible to focus multimode waves. The single and multi-layer experiments confirm the multi-layered focused ray model and phase differentiation theory. Furthermore, experiments are conducted to analyze the measured results.

Full area covered 3D profile measurement of special-shaped optics based on a new prototype non-contact profiler.

A new prototype non-contact profiler based on surface tracking has been specially developed. Surface tracking is carried out by a specially designed dual stage probe system with the aid of a four-Degree Of Freedom high-precision motion platform. The dual stage probe system keeps a short-range optical probe constantly tracking the surface by a self-developed voice coil motor servo, by which a wide measuring range of up to 10 mm is realized. The system performance evaluation including resolution, repeatability, and scanning speed proved the good capability of the new prototype non-contact profiler. To realize a full area covered 3D profile measurement of special-shaped optics within one scanning procedure, a signal intensity monitor integrated in the surface tracking controller is specially developed. In the experiment, a snip-single-corner-rectangular-shaped freeform surface was successfully measured over full area by the new non-contact profiler. This work provides an effective solution for 3D profile measurement of special-shaped optical surfaces over full reflecting area. Experimental results demonstrate that the proposed measuring system is of great significance in quality evaluation of optical surfaces.

Deconvolution imaging of weak reflective pipe defects using guided-wave signals captured by a scanning receiver.

Guided-wave echoes from weak reflective pipe defects are usually interfered by coherent noise and difficult to interpret. In this paper, a deconvolution imaging method is proposed to reconstruct defect images from synthetically focused guided-wave signals, with enhanced axial resolution. A compact transducer, circumferentially scanning around the pipe, is used to receive guided-wave echoes from discontinuities at a distance. This method achieves a higher circumferential sampling density than arrayed transducers-up to 72 sampling spots per lap for a pipe with a diameter of 180 mm. A noise suppression technique is used to enhance the signal-to-noise ratio. The enhancement in both signal-to-noise ratio and axial resolution of the method is experimentally validated by the detection of two kinds of artificial defects: a pitting defect of 5 mm in diameter and 0.9 mm in maximum depth, and iron pieces attached to the pipe surface. A reconstructed image of the pitting defect is obtained with a 5.87 dB signal-to-noise ratio. It is revealed that a high circumferential sampling density is important for the enhancement of the inspection sensitivity, by comparing the images reconstructed with different down-sampling ratios. A modified full width at half maximum is used as the criterion to evaluate the circumferential extent of the region where iron pieces are attached, which is applicable for defects with inhomogeneous reflection intensity.

A new method for evaluating the degeneration of articular cartilage using pulse-echo ultrasound.

This paper presents a novel nondestructive ultrasonic technique for measuring the sound speed and acoustic impedance of articular cartilage using the pulsed Vz,t technique. Vz,t data include a series of pulsed ultrasonic echoes collected using different distances between the ultrasonic transducer and the specimen. The 2D Fourier transform is applied to the Vz,t data to reconstruct the 2D reflection spectrum Rθ,ω. To obtain the reflection coefficient of articular cartilage, the Vz,t data from a reference specimen with a well-known reflection coefficient are obtained to eliminate the dependence on the general system transfer function. The ultrasound-derived aggregate modulus (Ha) is computed based on the measured reflection coefficient and the sound speed. In the experiment, 32 cartilage-bone samples were prepared from bovine articular cartilage, and 16 samples were digested using 0.25% trypsin solution. The sound speed and Ha of these cartilage samples were evaluated before and after degeneration. The magnitude of the sound speed decreased with trypsin digestion (from 1663 ± 5.6 m/s to 1613 ± 5.3 m/s). Moreover, the Young's modulus in the corresponding degenerative state was measured and was correlated with the ultrasound-derived aggregate modulus. The ultrasound-derived aggregate modulus was determined to be highly correlated with the Young's modulus (n = 16, r>0.895, p<0.003, Pearson correlation test for each measurement). The results demonstrate the effectiveness of using the proposed method to assess the changes in sound speed and the ultrasound-derived aggregate modulus of cartilage after degeneration.

Determination of the multiple local properties of thin layer with high lateral resolution by scanning acoustic microscopy.

Simultaneous determination of the multiple local acoustic and geometrical properties of the thin layer with a high lateral resolution is of great interest in ultrasonic non-destructive evaluation. In this paper, we propose a technique based on the V(z, t) data to simultaneously determine the four local properties of the thin layer, namely, the thickness, the sound velocity, the acoustic impedance, and the density. First, the V(z, t) data are collected from both the thin layer and the reference material. Then the sound velocity and the thickness are calculated by focusing the point-focusing transducer on the front and back surfaces of the thin layer, with the confocal positions determined by averaging the peak positions in the V(z) curves at different frequencies. Second, the acoustic impedance of the thin layer is obtained based on the experimental and theoretical two-dimensional reflection spectrum using the echo from the front surface of the layer. Finally, the density can be obtained by dividing the acoustic impedance by the sound velocity. The four local properties of an aluminum layer are accurately obtained using our method. The largest relative error of determining the four properties is around 1%. This technique opens a new way of simultaneously measuring the multiple local acoustic and geometrical properties of thin layers.

[CORBA-based design and packaging of picture archiving and communication system object].

Regionalization has become one of the most important trends in the development of picture archiving and communication systems (PACS) due to the existence of large amounts of information islands. The conventional PACS designed according to the DICOM standard on the basis of the C/S structure fails to meet the demand of regional information system maintenance. A regional PACS system based on common object request broker architecture (CORBA) distributed technology is therefore proposed and implemented. This article describes the design and packaging of the PACS objects. When mounting a series of separate logical and related functional PACS objects on the ORB bus, the multi-scale PACS systems can be established. This method eliminates the limitation of the C/S structure and offers good compatibility and scalability.