The Application of Digital Optical 3D Image Analyzer Evaskin in The Evaluation of Wrinkles

To verify the effectiveness of digital optical 3D image analyzer EvaSKIN in the objective and quantitative evaluation of wrinkles.A total of 115 subjects were recruited,the facial images of the subjects were collected by digital optical 3D image analyzer and manual camera,the changes of crow’s feet with age were analyzed.Pictures obtained by manual photography can be directly used for observation and preliminary grading of wrinkles.However,the requirements for evaluators are high,and the results are prone to errors,which will affect the accuracy of the evaluation.Therefore,skilled raters are needed.Compared with the manual photography method,the digital optical 3D image analyzer EvaSKIN can realize three-dimensional extraction of wrinkles,and obtain the change trend of crow’s feet with age.20~30 years old,wrinkles begin to appear slowly;wrinkles will increase rapidly at the age of 30~50;The length of 50~60 year old wrinkles is basically fixed,the wrinkles develop longitudewise,gradually widen and deepen,and the area,depth and volume increase is obvious,and the skin aging condition is intensified.the digital optical 3D image analyzer EvaSKIN realizes the 3D extraction of wrinkles,quantifies the circumference,area,average depth,maximum depth and volume of wrinkles,realizes the objective and quantitative evaluation of wrinkle state,is more accurate in the measurement of wrinkles,and provides a new instrument and method for the evaluation of wrinkles.it is a perfect and supplement to the traditional evaluation methods,and to a certain extent,it helps the research and development and evaluation institutions of cosmetics to obtain more abundant and three-dimensional data support.

DATA PROCESSING TECHNOLOGY OF AIRBORNE 3D IMAGE

Airborne 3D image which integrates GPS, attitude measurement unit (AMU), scanning laser rangefinder (SLR) and spectra scanner has been developed successfully. The spectral scanner and SLR use the same optical system which ensures laser point to match pixel seamlessly. The distinctive advantage of 3D image is that it can produce geo-referenced images and DSM (digital surface models) images without any ground control points (GCPs). It is no longer necessary to survey GCPs and with some softwares the data can be processed and produce digital surface models (DSM) and geo-referenced images in quasi-real-time, therefore the efficiency of 3D image is 10–100 times higher than that of traditional approaches. The processing procedure involves decomposing and checking the raw data, processing GPS data, calculating the positions of laser sample points, producing geo-referenced image, producing DSM and mosaicing strips. The principle of 3D image is first introduced in this paper, and then we focus on the fast processing technique and algorithms. The flight tests and processed results show that the processing technique is feasible and can meet the requirement of quasi-real-time applications.

Use of high-resolution X-ray computed tomography and 3D image analysis to quantify mineral dissemination and pore space in oxide copper ore particles

Mineral dissemination and pore space distribution in ore particles are important features that influence heap leaching performance. To quantify the mineral dissemination and pore space distribution of an ore particle, a cylindrical copper oxide ore sample (I center dot 4.6 mm x 5.6 mm) was scanned using high-resolution X-ray computed tomography (HRXCT), a nondestructive imaging technology, at a spatial resolution of 4.85 mu m. Combined with three-dimensional (3D) image analysis techniques, the main mineral phases and pore space were segmented and the volume fraction of each phase was calculated. In addition, the mass fraction of each mineral phase was estimated and the result was validated with that obtained using traditional techniques. Furthermore, the pore phase features, including the pore size distribution, pore surface area, pore fractal dimension, pore centerline, and the pore connectivity, were investigated quantitatively. The pore space analysis results indicate that the pore size distribution closely fits a log-normal distribution and that the pore space morphology is complicated, with a large surface area and low connectivity. This study demonstrates that the combination of HRXCT and 3D image analysis is an effective tool for acquiring 3D mineralogical and pore structural data.

Reduced Imaging Time and Improved Image Quality of 3D Isotropic T2-Weighted Magnetic Resonance Imaging with Compressed Sensing for the Female Pelvis

This study is to compare three-dimensional(3D)isotropic T2-weighted magnetic resonance imaging(MRI)with compressed sensing-sampling perfection with application optimized contrast(CS-SPACE)and the conventional image(3D-SPACE)sequence in terms of image quality,estimated signal-to-noise ratio(SNR),relative contrast-to-noise ratio(CNR),and the lesions’conspicuous of the female pelvis.Thirty-six females(age:51,28-73)with cervical carcinoma(n=20),rectal carcinoma(n=7),or uterine fibroid(n=9)were included.Patients underwent magnetic resonance(MR)imaging at a 3T scanner with the sequences of 3D-SPACE,CS-SPACE,and twodimensional(2D)T2-weighted turbo-spin echo(TSE).Quantitative analyses of estimated SNR and relative CNR between tumors and other tissues,image quality,and tissue conspicuity were performed.Two radiologists assessed the difference in diagnostic findings for carcinoma.Quantitative values and qualitative scores were analyzed,respectively.The estimated SNR and the relative CNR of tumor-to-muscle obturator internus,tumor-to-myometrium,and myometrium-to-muscle obturator internus was comparable between 3D-SPACE and CS-SPACE.The overall image quality and the conspicuity of the lesion scores of the CS-SPACE were higher than that of the 3D-SPACE(P<0.01).The CS-SPACE sequence offers shorter scan time,fewer artifacts,and comparable SNR and CNR to conventional 3D-SPACE,and has the potential to improve the performance of T2-weighted images.

Digital Refocusing: All-in-Focus Image Rendering Based on Holoscopic 3D Camera

This paper presents an innovative method for digital refocusing of different point in space after capturing and also extracts all-in-focus image. The proposed method extracts all-in-focus image using Michelson contrast formula hence, it helps in calculating the coordinates of the 3D object location. With light field integral camera setup the scene to capture the objects precisely positioned in a measurable distance from the camera therefore, it helps in refocusing process to return the original location where the object is focused;else it will be blurred with less contrast. The highest contrast values at different points in space can return the focused points where the objects are initially positioned as a result;all-in-focus image can also be obtained. Detailed experiments are conducted to demonstrate the credibility of proposed method with results.

3D displays: toward holographic video displays of 3D images

As the fiat panel displays （Liquid Crystal Displays, AMOLED, etc.） reach near perfection in their viewing qualities and display areas, it is natural to seek the next level of displays, including 3D displays. There is a strong surge in 3D liquid crystal displays as a result of the successful movie Avatar. Most of these 3D displays involve the employment of special glasses that allow one view perspective for each of the eyes to achieve a depth perception. Such displays are not real 3D displays. In fact, these displays can only provide one viewing perspective for all viewers, regardless of the viewer＇s position. In addition, a fundamental viewing problem of focusing and accommodation exist that can lead to discomfort and fatigue for many viewers. In this paper, the authors review the current status of stereoscopic 3D displays and their problems. The authors will also discuss the possibility of using fiat panels for the display of both phase and intensity of video image information, leading to the ultimate display of 3D holographic video images. Many of the fundamental issues and limitations will be presented and discussed.

Computer generated hologram from full-parallax 3D image data captured by scanning vertical camera array(Invited Paper)

Full-parallax light-field is captured by a small-scale 3D image scanning system and applied to holographic display. A vertical camera array is scanned horizontally to capture full-parallax imagery, and the vertical views between cameras are interpolated by depth image-based rendering technique. An improved technique for depth estimation reduces the estimation error and high-density light-field is obtained. The captured data is employed for the calculation of computer hologram using ray-sampling plane. This technique enables high-resolution display even in deep 3D scene although a hologram is calculated from ray information, and thus it makes use of the important advantage of holographic 3D display.

Research on Clothing Simulation Design Based on Three-Dimensional Image Analysis

Traditional clothing design models based on adaptive meshes cannot reflect.To solve this problem,a clothing simulation design model based on 3D image analysis technology is established.The model uses feature extraction and description of image evaluation parameters,and establishes the mapping relationship between image features and simulation results by using the optimal parameter values,thereby obtaining a three-dimensional image simulation analysis environment.On the basis of this model,by obtaining the response results of clothing collision detection and the results of local adaptive processing of clothing meshes,the cutting form and actual cutting effect of clothing are determined to construct a design model.The simulation results show that compared with traditional clothing design models,clothing simulation design based on 3D image analysis technology has a better effect,with the definition of fabric folds increasing by 40%.More striking contrast between light and dark,the resolution increasing by 30%,and clothing details getting a more real manifestation.

Fast calculation of wave front amplitude propagation: a tool to analyze the 3D image on a hologram(Invited Paper)

A simple approach to calculate the amplitude component of a wave front propagating in space from a hologram is proposed. It is able to calculate the amplitude distribution on a plane at any distance rapidly using a standard GPU. This is useful for analyzing and reconstructing the 3D image encoded on a hologram.

3D Medical Image Interpolation Based on Parametric Cubic Convolution

In the process of display, manipulation and analysis of biomedical image data, they usually need to be converted to data of isotropic discretization through the process of interpolation, while the cubic convolution interpolation is widely used due to its good tradeoff between computational cost and accuracy. In this paper, we present a whole concept for the 3D medical image interpolation based on cubic convolution, and the six methods, with the different sharp control parameter,which are formulated in details. Furthermore, we also give an objective comparison for these methods using data sets with the different slice spacing. Each slice in these data sets is estimated by each interpolation method and compared with the original slice using three measures: mean-squared difference, number of sites of disagreement, and largest difference. According to the experimental results, we present a recommendation for 3D medical images under the different situations in the end.

Uniaxial experimental study of the acoustic emission and deformation behavior of composite rock based on 3D digital image correlation(DIC)

In this paper, uniaxial compression tests were carried out on a series of composite rock specimens with different dip angles, which were made from two types of rock-like material with different strength. The acoustic emission technique was used to monitor the acoustic signal characteristics of composite rock specimens during the entire loading process. At the same time, an optical non-contact 3 D digital image correlation technique was used to study the evolution of axial strain field and the maximal strain field before and after the peak strength at different stress levels during the loading process. The effect of bedding plane inclination on the deformation and strength during uniaxial loading was analyzed. The methods of solving the elastic constants of hard and weak rock were described. The damage evolution process, deformation and failure mechanism, and failure mode during uniaxial loading were fully determined. The experimental results show that the θ = 0?–45?specimens had obvious plastic deformation during loading, and the brittleness of the θ = 60?–90?specimens gradually increased during the loading process. When the anisotropic angle θincreased from 0?to 90?, the peak strength, peak strain,and apparent elastic modulus all decreased initially and then increased. The failure mode of the composite rock specimen during uniaxial loading can be divided into three categories:tensile fracture across the discontinuities(θ = 0?–30?), slid-ing failure along the discontinuities(θ = 45?–75?), and tensile-split along the discontinuities(θ = 90?). The axial strain of the weak and hard rock layers in the composite rock specimen during the loading process was significantly different from that of the θ = 0?–45?specimens and was almost the same as that of the θ = 60?–90?specimens. As for the strain localization highlighted in the maximum principal strain field, the θ = 0?–30?specimens appeared in the rock matrix approximately parallel to the loading direction,while in the θ = 45?–90?specimens it appeared at the hard and weak rock layer interface.

3D Particle Image Velocimetry Test of Inner Flow in a Double Blade Pump Impeller

The double blade pump is widely used in sewage treatment industry,however,the research on the internal flow characteristics of the double blade pump with particle image velocimetry（PIV） technology is very little at present.To reveal inner flow characteristics in double blade pump impeller under off-design and design conditions,inner flows in a double blade pump impeller,whose specific speed is 111,are measured under the five off-design conditions and design condition by using 3D PIV test technology.In order to ensure the accuracy of the 3D PIV test,the external trigger synchronization system which makes use of fiber optic and equivalent calibration method are applied.The 3D PIV relative velocity synthesis procedure is compiled by using Visual C＋＋ 2005.Then absolute velocity distribution and relative velocity distribution in the double blade pump impeller are obtained.Test results show that vortex exists in each condition,but the location,size and velocity of vortex core are different.Average absolute velocity value of impeller outlet increases at first,then decreases,and then increases again with increase of flow rate.Again average relative velocity values under 0.4,0.8,and 1.2 design condition are higher than that under 1.0 design condition,while under 0.6 and 1.4 design condition it is lower.Under low flow rate conditions,radial vectors of absolute velocities at impeller outlet and blade inlet near the pump shaft decrease with increase of flow rate,while that of relative velocities at the suction side near the pump shaft decreases.Radial vectors of absolute velocities and relative velocities change slightly under the two large flow rate conditions.The research results can be applied to instruct the hydraulic optimization design of double blade pumps.

A 128×128 SPAD LiDAR sensor with column-parallel 25 ps resolution TA-ADCs

This paper presents a design of single photon avalanche diode(SPAD)light detection and ranging(LiDAR)sensor with 128×128 pixels and 128 column-parallel time-to-analog-merged-analog-to-digital converts(TA-ADCs).Unlike the conventional TAC-based SPAD LiDAR sensor,in which the TAC and ADC are separately implemented,we propose to merge the TAC and ADC by sharing their capacitors,thus avoiding the analog readout noise of TAC’s output buffer,improving the conversion rate,and reducing chip area.The reverse start-stop logic is employed to reduce the power of the TA-ADC.Fabricated in a 180 nm CMOS process,our prototype sensor exhibits a timing resolution of 25 ps,a DNL of+0.30/−0.77 LSB,an INL of+1.41/−2.20 LSB,and a total power consumption of 190 mW.A flash LiDAR system based on this sensor demonstrates the function of 2D/3D imaging with 128×128 resolution,25 kHz inter-frame rate,and sub-centimeter ranging precision.

DIRECT VOXEL-PROJECTION FOR VOLUMETRIC DATA RENDERING IN MEDICAL IMAGERY

The volumetric rendering of 3 D medical image data is very effective method for communication about radiological studies to clinicians. Algorithms that produce images with artifacts and inaccuracies are not clinically useful. This paper proposed a direct voxel projection algorithm to implement volumetric data rendering. Using this algorithm, arbitrary volume rotation, transparent and cutaway views are generated satisfactorily. Compared with the existing raytracing methods, it improves the projection image quality greatly. Some experimental results about real medical CT image data demonstrate the advantages and fidelity of the proposed algorithm.

Short‐term and long‐term memory self‐attention network for segmentation of tumours in 3D medical images

Tumour segmentation in medical images(especially 3D tumour segmentation)is highly challenging due to the possible similarity between tumours and adjacent tissues,occurrence of multiple tumours and variable tumour shapes and sizes.The popular deep learning‐based segmentation algorithms generally rely on the convolutional neural network(CNN)and Transformer.The former cannot extract the global image features effectively while the latter lacks the inductive bias and involves the complicated computation for 3D volume data.The existing hybrid CNN‐Transformer network can only provide the limited performance improvement or even poorer segmentation performance than the pure CNN.To address these issues,a short‐term and long‐term memory self‐attention network is proposed.Firstly,a distinctive self‐attention block uses the Transformer to explore the correlation among the region features at different levels extracted by the CNN.Then,the memory structure filters and combines the above information to exclude the similar regions and detect the multiple tumours.Finally,the multi‐layer reconstruction blocks will predict the tumour boundaries.Experimental results demonstrate that our method outperforms other methods in terms of subjective visual and quantitative evaluation.Compared with the most competitive method,the proposed method provides Dice(82.4%vs.76.6%)and Hausdorff distance 95%(HD95)(10.66 vs.11.54 mm)on the KiTS19 as well as Dice(80.2%vs.78.4%)and HD95(9.632 vs.12.17 mm)on the LiTS.

Research on a bifurcation location algorithm of a drainage tube based on 3D medical images

Based on patient computerized tomography data,we segmented a region containing an intracranial hematoma using the threshold method and reconstructed the 3D hematoma model.To improve the efficiency and accuracy of identifying puncture points,a point-cloud search arithmetic method for modified adaptive weighted particle swarm optimization is proposed and used for optimal external axis extraction.According to the characteristics of the multitube drainage tube and the clinical needs of puncture for intracranial hematoma removal,the proposed algorithm can provide an optimal route for a drainage tube for the hematoma,the precise position of the puncture point,and preoperative planning information,which have considerable instructional significance for clinicians.

Study on threshold segmentation of multi-resolution 3D human brain CT image

In order to effectively improve the pathological diagnosis capability and feature resolution of 3D human brain CT images,a threshold segmentation method of multi-resolution 3D human brain CT image based on edge pixel grayscale feature decomposition is proposed in this paper.In this method,first,original 3D human brain image information is collected,and CT image filtering is performed to the collected information through the gradient value decomposition method,and edge contour features of the 3D human brain CT image are extracted.Then,the threshold segmentation method is adopted to segment the regional pixel feature block of the 3D human brain CT image to segment the image into block vectors with high-resolution feature points,and the 3D human brain CT image is reconstructed with the salient feature point as center.Simulation results show that the method proposed in this paper can provide accuracy up to 100%when the signal-to-noise ratio is 0,and with the increase of signal-to-noise ratio,the accuracy provided by this method is stable at 100%.Comparison results show that the threshold segmentation method of multi-resolution 3D human brain CT image based on edge pixel grayscale feature decomposition is signicantly better than traditional methods in pathological feature estimation accuracy,and it effectively improves the rapid pathological diagnosis and positioning recognition abilities to CT images.

Application of Opening and Closing Morphology in Deep Learning-Based Brain Image Registration

In order to improve the registration accuracy of brain magnetic resonance images(MRI),some deep learning registration methods use segmentation images for training model.How-ever,the segmentation values are constant for each label,which leads to the gradient variation con-centrating on the boundary.Thus,the dense deformation field(DDF)is gathered on the boundary and there even appears folding phenomenon.In order to fully leverage the label information,the morphological opening and closing information maps are introduced to enlarge the non-zero gradi-ent regions and improve the accuracy of DDF estimation.The opening information maps supervise the registration model to focus on smaller,narrow brain regions.The closing information maps supervise the registration model to pay more attention to the complex boundary region.Then,opening and closing morphology networks(OC_Net)are designed to automatically generate open-ing and closing information maps to realize the end-to-end training process.Finally,a new registra-tion architecture,VM_(seg+oc),is proposed by combining OC_Net and VoxelMorph.Experimental results show that the registration accuracy of VM_(seg+oc) is significantly improved on LPBA40 and OASIS1 datasets.Especially,VM_(seg+oc) can well improve registration accuracy in smaller brain regions and narrow regions.

An ellipse detection method for 3D head image fusion based on color-coded mark points

In this paper, we proposed a new kind of mark points coded by color and a new quasi-ellipse detector on pixel level. This method is especially applicable to three- dimensional （3D） head panoramic reconstruction. Images of adjacent perspectives can be stitched by matching pasted color-coded mark points in overlap area to calculate the transformation matrix. This paper focuses on how the color-coded mark points work and how to detect and match corresponding points from different perspectives. Tests are performed to show the efficiency and accuracy of this method based on the original data obtained by structured light projection.