Pseudo-color Processing Research Articles

Four-phase CT lesion recognition based on multi-phase information fusion framework and spatiotemporal prediction module

Multiphase information fusion and spatiotemporal feature modeling play a crucial role in the task of four-phase CT lesion recognition. In this paper, we propose a four-phase CT lesion recognition algorithm based on multiphase information fusion framework and spatiotemporal prediction module. Specifically, the multiphase information fusion framework uses the interactive perception mechanism to realize the channel-spatial information interactive weighting between multiphase features. In the spatiotemporal prediction module, we design a 1D deep residual network to integrate multiphase feature vectors, and use the GRU architecture to model the temporal enhancement information between CT slices. In addition, we employ CT image pseudo-color processing for data augmentation and train the whole network based on a multi-task learning framework. We verify the proposed network on a four-phase CT dataset. The experimental results show that the proposed network can effectively fuse the multi-phase information and model the temporal enhancement information between CT slices, showing excellent performance in lesion recognition.

The Effect of Different Image Processing Techniques on the Measurement Accuracy of Endodontics File Length.

Different software capabilities have been used in digital systems to increase the diagnostic quality of radiographic projections. Considering the availability of different enhancement techniques, it is necessary to determine the suitability of each technique for various diagnostic cases. There is controversy between studies over the effect of different digital enhancement techniques on the accuracy of file length measurements in endodontics. The present in vitro study aimed to determine the effect of the software capabilities on the diagnostic accuracy to determine endodontic file lengths in photostimulable phosphor (PSP) radiographs. In the present in vitro study, standard access cavities were prepared in 44 extracted human single-rooted permanent teeth. An endodontic file was placed in each root canal. PSP sensors were used for digital imaging using the parallel technique. All the images were reviewed on a same monitor; once normally with no software enhancement and once using software manipulations including pseudo-color, sharpness, emboss, and edge enhancement. The distance from the file tip to the rubber stop was measured on the images by an electronic ruler. Significantly, all of the image enhancement techniques presented shorter measurements comparing to the actual length. The results revealed the significant accuracy of the measured error in the pseudo-color enhancement technique compared to other techniques. The results revealed significant differences between the initial measurements (the gold standard) and those made on the manipulated radiographs. In all cases, the measurements were significantly lower than the real values. Therefore, none of these digital enhancement techniques can increase the accuracy of file length measurements significantly. However, manipulation with the pseudo-color option resulted in fewer errors compared to other options and the normal images. Hence, for precise measurements of the endodontic file lengths, pseudo-color processing algorithm can be suggested when using PSP sensors.

Multi-scale detection of pulmonary nodules by integrating attention mechanism

The detection of pulmonary nodules has a low accuracy due to the various shapes and sizes of pulmonary nodules. In this paper, a multi-scale detection network for pulmonary nodules based on the attention mechanism is proposed to accurately predict pulmonary nodules. During data processing, the pseudo-color processing strategy is designed to enhance the gray image and introduce more contextual semantic information. In the feature extraction network section, this paper designs a basic module of ResSCBlock integrating attention mechanism for feature extraction. At the same time, the feature pyramid structure is used for feature fusion in the network, and the problem of the detection of small-size nodules which are easily lost is solved by multi-scale prediction method. The proposed method is tested on the LUNA16 data set, with an 83% mAP value. Compared with other detection networks, the proposed method achieves an improvement in detecting pulmonary nodules.

An improved re-parameterized visual geometry group network for rolling bearing fault diagnosis.

The spectrum of data-driven fault diagnosis models is greatly expanded by deep learning. However, classical convolution and multiple branching structures have their faults in computational complexity and feature extraction. To address these issues, we propose an improved re-parameterized visual geometry group (VGG) network (RepVGG) for rolling bearing fault diagnosis. In order to meet the requirements of neural networks for the amount of data, data augmentation is performed to increase the amount of original data. Then, the original one-dimensional vibration signal is processed into a single-channel time-frequency image using the short-time Fourier transform and converted into a three-channel color time-frequency image using pseudo-color processing technology. Finally, the RepVGG model with an embedded convolutional block attention mechanism structure is developed to extract defect features from three-channel time-frequency images and perform defect classification. Two datasets of vibration data from rolling bearings are used to demonstrate the strong adaptability of this method compared with other methods.

Imbibition Characteristic of Fractured Tight Sandstone Reservoir

“Fracture network stimulation + imbibition replacement” is a new attempt to effectively develop tight sandstone reservoirs, and the fractures provide conditions for fluid imbibition replacement. On the basis of nuclear magnetic resonance and pseudo-color processing technology, combined with the imbibition experiments, this paper studies the imbibition process of fractured tight sandstone reservoirs, clarifies the effect of each level of pore-throat on imbibition, and realizes the visualization of the imbibition process. The results show that, in fractured tight sandstone reservoirs, the fluid displacement occurs in fractures first, followed by pore-throat. Most of the imbibition recovery is contributed by the macropore, the contribution of the mesopore to imbibition recovery is very weak, and the contributions of the micropore and the pinhole are even less. In the process of imbibition, capillary force and gravitational force are key parameters controlling fluid flow in pores and fractures. The replacement of fluid normally takes place in the early stage of imbibition, especially on the first day of imbibition, then the imbibition rate gradually decreases and finally tends to be stable.

A novel approach for 3D in situ visualization of morphological changes in dilute sulfuric acid-pretreated straw by micro-computed tomography

Lignocellulosic biomass is a crucial agricultural and industrial product. Dilute acid pretreatment is a common step to break down the dense and complex lignocellulose-based structure of straw to enhance its biochemical conversion efficiency. The straw derived from diverse crops, such as corn, cotton, and rape, displays diverse internal morphologies and varying responses to pretreatment methods. It is, therefore, necessary to understand the underlying mechanisms of these microstructural changes, to maximize their industrial value. This is the first study to demonstrate X-ray micro-computed tomography (micro-CT) based 3D visualization to observe the changes in the histology of straw caused by pretreatment using dilute acids, understand the mechanism of dilute sulfuric acid pretreatment, and visualize the reason behind the resulting morphological changes in the microstructure of straw. Three types of straw from corn, cotton, and rape were treated with 1.5% (w/w) dilute sulfuric acid at 121 °C for 30 and 60 min. Subsequently, the straw samples were imaged using Skyscan1275 under optimized micro-CT scan and image reconstruction conditions. In addition, the algorithms for image segmentation were determined. Volume- and slice-rendered images were analyzed via pseudo-color processing for different straw samples. Furthermore, the results of the micro-CT 3D in situ visualization aligned with the chemical analysis of lignocellulose composition. Overall, the presented non-invasive 3D micro-CT technique can provide crucial insights into the morphology and thus microstructural changes of lignocellulose-based materials not only qualitatively, but also semi-quantitatively. The non-invasive imaging methodology described in the present study will prove to be extremely helpful in prompt in situ analysis and comparison of diverse treatment approaches using lignocellulosic biomass.

Study on the Imbibition Characteristics of Different Types of Pore-Throat Based on Nuclear Magnetic Resonance Technology

“Fracturing network+imbibition oil production” is a new attempt to effectively develop low-permeability tight reservoirs. Fracturing fluid is not only a carrier for sand carrying but also a tool in the process of imbibition. On the basis of imbibition experiments, combined with nuclear magnetic resonance and pseudo-color processing technology, this paper clarified the dominant forces of different types of pore-throat and quantitatively characterized the contribution of different levels of pore-throat to imbibition oil recovery. The results show that gravity is the main controlling force of imbibition for reservoirs with higher permeability. Fluid replacement mainly occurs in the early period of imbibition. Macropores contribute most of the imbibition recovery, mesopores have a weak contribution, and the contribution of micropores and pinholes can be ignored. For the reservoirs with low permeability, capillary force is the main controlling force of imbibition. Fluid replacement mainly occurs in the later period of imbibition. Macropores contribute most of the imbibition recovery rate, mesopores contribute a small part of the imbibition recovery factor, and the contribution of micropores and pinholes can be ignored. This paper clarified that macropores and mesopores are the main sources of the contribution of imbibition recovery efficiency, and oil content and connectivity are key factors for the imbibition recovery efficiency.

Research on detection method of bleeding point in two-dimensional DSA image based on parametric color imaging

Digital Subtraction Angiography (DSA) has become an essential method in diagnosing and detecting vascular bleeding points. According to the frame number sequence, doctors subjectively analyze gray-black DSA data to diagnose vascular bleeding points. This study carried out parametric color imaging processing on the original two-dimensional DSA image sequence to assist doctors in judging blood vessel bleeding more accurately and quickly on angiography results and obtain quantitative standards. Five parameter values are calculated by enhancing the two-dimensional DSA image, segmenting the blood vessel area of the two-dimensional DSA image, and fitting the time-concentration curve. The parameters include AUC, time to peak, development time, transit time, and flow rate of contrast agent. The parameter value determines the gray value of the image pixel point and generates a color image with corresponding parameters through image pseudo-color processing. The color imaging results of each parameter of 33 groups of simulated hemorrhage data in-vitro and DSA data of 42 cases of vascular bleeding points determine the selection of parameters to assist in diagnosing vascular bleeding points, and the experimental results finally select the development time parameter color imaging result map to assist doctors in diagnosing blood vessel bleeding points.

Real-Time Φ-OTDR Vibration Event Recognition Based on Image Target Detection.

Accurate and fast identification of vibration signals detected based on the phase-sensitive optical time-domain reflectometer (Φ-OTDR) is crucial in reducing the false-alarm rate of the long-distance distributed vibration warning system. This study proposes a computer vision-based Φ-OTDR multi-vibration events detection method in real-time, which can effectively detect perimeter intrusion events and reduce personnel patrol costs. Pulse accumulation, pulse cancellers, median filter, and pseudo-color processing are employed for vibration signal feature enhancement to generate vibration spatio-temporal images and form a customized dataset. This dataset is used to train and evaluate an improved YOLO-A30 based on the YOLO target detection meta-architecture to improve system performance. Experiments show that using this method to process 8069 vibration data images generated from 5 abnormal vibration activities for two types of fiber optic laying scenarios, buried underground or hung on razor barbed wire at the perimeter of high-speed rail, the system mAP@.5 is 99.5%, 555 frames per second (FPS), and can detect a theoretical maximum distance of 135.1 km per second. It can quickly and effectively identify abnormal vibration activities, reduce the false-alarm rate of the system for long-distance multi-vibration along high-speed rail lines, and significantly reduce the computational cost while maintaining accuracy.

Interactive System Based on Leap Motion for 3D Medical Model

An interactive visualization of the patients’ 3D medical anatomical model as guide is often helpful for doctors during complex surgery. However, there are certain limitations according to the actual requirements of building sterile operating environment. Traditional human–computer interaction tools (mouse and keyboard) must be disinfected regularly and cannot be used in the process. A noncontact gesture control medical model based on Leap Motion is proposed in this study. The gesture is recognized and localized without using mouse and keyboards through a binocular camera assembled on Leap Motion. Hence, the model is directly controlled by the gesture to complete the operation of rotation, zoom, and other functions. In this study, a 3D heart model is combined with pseudo-color processing technology to enhance the observability of its 3D structure. Gesture recognition technology is then utilized to control the rendered model as rotation and zoom. Experimental results show that our system has an absolute accuracy in recognizing circle, swipe, and other actions. Thus, rotation is proposed as a new motion that can be identified steadily. Rotation plays an essential role in usability, intuition, and interactive efficiency of future system design. The system is applicable to sterile operating environments due to its stable recognition process and small space occupation.

Dichroic Polarizing Metasurfaces for Color Control and Pseudo-Color Encoding

In ultracompact image displays based on metasurfaces, the image color is usually controlled by varied nanostructure dimensions, which requires elaborate design and precise manufacturing of nanostructures. Here, we present a metasurface composed of equal-sized nanostructures to control the color of output light, simply by polarization control. Specifically, with resonances occurring in two orthogonal axes for different wavelengths, each nanostructure of the metasurface acts as a biaxial nano-polarizer and reflect most of incident red and green light polarized along the long and short axes, respectively. Hence, by means of reconfiguring the orientations of the biaxial nano-polarizers, the mixture of red and green light with different intensity ratio, governed by Malus law, can be employed to generate a pseudo-colored nanoprinting image. We experimentally demonstrate the proposed metasurfaces by successfully encoding and decoding pseudo-color nanoprinting images right at the metasurfaces. With advantages such as flexible image display and ultra-simple nanostructure design, the proposed dichroic polarizing metasurface can promote advanced research of metasurfaces in color control, ultracompact image display, pseudo-color processing, and many other related fields.

Real-Time Detection on SPAD Value of Potato Plant Using an In-Field Spectral Imaging Sensor System.

In this study, a SPAD value detection system was developed based on a 25-wavelength spectral sensor to give a real-time indication of the nutrition distribution of potato plants in the field. Two major advantages of the detection system include the automatic segmentation of spectral images and the real-time detection of SPAD value, a recommended indicating parameter of chlorophyll content. The modified difference vegetation index (MDVI) linking the Otsu algorithm (OTSU) and the connected domain-labeling (CDL) method (MDVI–OTSU–CDL) is proposed to accurately extract the potato plant. Additionally, the segmentation accuracy under different modified coefficients of MDVI was analyzed. Then, the reflectance of potato plants was extracted by the segmented mask images. The partial least squares (PLS) regression was employed to establish the SPAD value detection model based on sensitive variables selected using the uninformative variable elimination (UVE) algorithm. Based on the segmented spectral image and the UVE–PLS model, the visualization distribution map of SPAD value was drawn by pseudo-color processing technology. Finally, the testing dataset was employed to measure the stability and practicality of the developed detection system. This study provides a powerful support for the real-time detection of SPAD value and the distribution of crops in the field.

Analysis of Coal Swelling Deformation Caused by Carbon Dioxide Adsorption Based on X-Ray Computed Tomography

The geologic sequestration of carbon dioxide by coal beds leads to the swelling deformation of coal. In order to investigate the swelling deformation characteristics at the microscopic scale, X-ray computed tomography (CT) scanning technology was used. X-ray CT scanning technology detects the internal structure, deformation, and porosity of coal at different gas pressures. Results show that swelling deformation is nonuniform, which is caused by the heterogeneity of the coal structure. Through quantitative measurement of the distance between fractures and pseudocolor processing of CT images, we observed that fractures gradually close with the increase of adsorption pressure. As adsorption pressure increases, the porosity of coal decreases, and the density of coal increases.

Study on Bohai sea ice based on MODIS data

Based on MODIS L1B data, we identify information of sea ice area, peripheral line and density, and also use Landsat data with higher resolution to verify the results obtained from MODIS data. Using pseudo color processing technology is more intuitive and more clear to show the various information of the Bohai sea. The whole process of sea ice information extraction is described in detail from MODIS data downloads to image processing and analysis. The selected data basically cover the entire process from the initial ice age, the peak ice age to the final ice age. The ideal results are obtained, and it also shows that the MODIS satellite data is feasible to monitor sea ice, which provides a reference for the establishment of monitoring sea ice model.

HYPERSPECTRAL CLASSIFICATION FOR IDENTIFYING DECAYED ORANGES INFECTED BY FUNGI

Fast and nondestructive detection of early decay caused by fungal infection in citrus fruit was a challenging task for the citrus industry during the postharvest fruit processing. In general, workers relied on the ultraviolet induction fluorescence technique to detect and remove the decayed citrus fruits in fruit packing houses. However, this operation was harmful for human health, and was also very inefficient. In this study, navel oranges were used as research object. A novel method combining with hyperspectral imaging technology in the wavelength region between 400 and 1100 nm wavelength was proposed to solve this problem. First, normalization approaches were applied to decrease the variation of spectral reflectance intensity due to natural curvature of navel orange surface. Then, the spectral data of regions of interest (ROIs) from normal and decayed tissues was analyzed by principal component analysis (PCA) for investigating the performance of visible and near infrared (Vis-NIR) hyperspectral data to discriminate these two kinds of tissues. Next, six characteristic wavelength images were obtained by analyzing the loadings of the first principal component (PC1). And, a multispectral image was established by using the corrected six characteristic wavelength images. On basis of the multispectral image, pseudo-color image processing with intensity slicing was utilized to produce a two-dimensional color image with clear contrast between decayed and normal tissues. Finally, an image segmentation algorithm by combining the pseudo-color processing method and a global threshold method was proposed for fast identification of decayed navel oranges. For 240 independent samples, the success rates were 100 and 97.5% for decayed navel oranges infected by Penicillium digitatum and normal navel oranges, respectively. In particular, the proposed algorithm was also applied to detect the decayed navel oranges infected by Penicillium italicum (samples not used for the development of algorithm) and obtained a 91.7% identification accuracy, indicating a well generalization ability and actual application value of the proposed algorithm.

Use and Analysis of Color Models in Image Processing

The use of color image processing is divided by two factors. First color is used in object identification and simplifies extraction from a scene and color is powerful descriptor. Second, humans can use thousands of color shades and intensities. Color Image Processing is divided into two areas full color and pseudo-color processing. In this processing various color models are used that are based on color recognition, color components etc. A few papers on various applications such as lane detection, face detection, fruit quality evaluation etc based on these color models have been published. A survey on widely used models RGB, HSI, HSV, RGI, etc. is represented in this paper.

Quantum image pseudocolor coding based on the density-stratified method

Pseudocolor processing is a branch of image enhancement. It dyes grayscale images to color images to make the images more beautiful or to highlight some parts on the images. This paper proposes a q...

A Novel Multi-Planar Fusion System for PET/CT Images

Objective To propose a PET/CT multi-planar fusion system based on PACS. Methods Firstly, the system got PET and CT slices and relevant DICOM header information from PACS workstation, preprocessed them and formed CT volume and PET volume, and then displayed the axial, coronal and sagittal planes of the two volumes by MPR. Afterwards, the results of MPR were enhanced by pseudo color processing, then were fused with the MRP results of CT correspondingly. Finally, the SUVs of PET images and the CT value of CT images were calculated according to the parameters obtained from the DICOM header, and were displayed in the lower right corner of the current sub window. Results This system can be integrated into PACS workstation expediently, can reconstruct each volume, either MPR or MIP, stably and effectively, and can fuse PET images with CT images in different planes. The resource consumption of the system is reasonable and the SUVs calculated were accurate and reliable. Conclusion The system is easy to use and has stable performance, which is helpful in the clinical diagnosis of malignant lesions as an auxiliary tool.

Enhancement Algorithm Combining Pseudocolor Processing and Marker-Based Watershed Transform for Medical Image

Medical images play a very important role in clinical medicine. They often have the features of low contrast, narrow gray scale and edge blurring between tissues. Aimed at the disadvantages, the paper presents a new medical image enhancement algorithm combining pseudocolor processing and marker-based watershed transform. The new algorithm and traditional pseudocolor processing in frequency domain are implemented using MATLAB, and their effectivity is evaluated by two parameters, mean and entropy. Results show that the proposed enhancement algorithm can improve the visual effect of different types of medical images, especially for the tissues in the low contrast regions in the image. The output image is more suitable for doctor’s diagnosing. The algorithm has been used in the medical image fusion system we developed, and the performance is very satisfactory.

An Image Fusion Algorithm Based on Pseudo-Color

The pseudo-color processing for target identification and tracking is very meaningful Experimental results show that the pseudo-color image fusion is a very effective methods. This paper presents a false color image fusion based on the new method. Fusion using wavelet transform grayscale images, find the gray fused image and the difference between the original image, respectively, as the image of l, α, β components are color fusion image, and then after the color transformation, the final false color fused image. The results showed that the color fusion image colors more vivid, more in line with human visual characteristics.