Gray Value Changes Research Articles

Adaptive Image-Defogging Algorithm Based on Bright-Field Region Detection

Image defogging is an essential technology used in traffic safety monitoring, military surveillance, satellite and remote sensing image processing, medical image diagnostics, and other applications. Current methods often rely on various priors, with the dark-channel prior being the most frequently employed. However, halo and bright-field color distortion issues persist. To further improve image quality, an adaptive image-defogging algorithm based on bright-field region detection is proposed in this paper. Modifying the dark-channel image improves the abrupt changes in gray value in the traditional dark-channel image. By setting the first and second lower limits of transmittance and introducing an adaptive correction factor to adjust the transmittance of the bright-field region, the limitations of the dark-channel prior in extensive ranges and high-brightness areas can be significantly alleviated. In addition, a guide filter is utilized to enhance the initial transmittance image, preserving the details of the defogged image. The results of the experiment demonstrate that the algorithm presented in this paper effectively addresses the mentioned issues and has shown outstanding performance in both objective evaluation and subjective visual effects.

Evaluation of the effects of different bracket types on the detection of interproximal enamel caries using periapical radiography

Aim: During orthodontic treatment, dental materials can affect the imaging of caries lesions. Material density and X-ray beam attenuation play important roles in this imaging. This study aims to evaluate the artifacts that are caused by brackets made of different materials and affect the visibility of International Caries Detection and Assessment System (ICDAS) code 5 caries. Methodology: One premolar tooth with ICDAS code 5 caries was examined. Eight periapical radiographs were taken: one without a bracket and seven with different types of brackets (composite with metal slot, self-ligating ceramic, monocrystalline ceramic, polycrystalline ceramic, zirconium, self-ligating stainless steel, and conventional stainless steel). The gray values of the caries region were evaluated using Fiji software (version 1.53f, National Institutes of Health, USA) on periapical radiographs. Results: Conventional stainless steel and self-ligating stainless steel brackets increased the radiopacity of the outer half of the enamel (E1). When these brackets were present, the gray values changed by -13.63633 (p = .026) and -16.38967 (p = .006), respectively. There was no statistically significant difference in column B due to the brackets. However, numerically, the gray value changes were similar to those in column A. Conclusion: Orthodontic brackets affect the evaluation of periapical images. Ceramic brackets provide more advantages than stainless steel brackets for radiographic imaging. How to cite this article: Karabiber G, Arsan B, Kocaer AF. Evaluation of the effects of different bracket types on the detection of interproximal enamel caries using periapical radiography. Int Dent Res 2023;13(2):83-89. https://doi.org/10.5577/idr.2023.vol13.no2.6 Linguistic Revision: The English in this manuscript has been checked by at least two professional editors, both native speakers of English.

Magnetic nanoparticle loaded biodegradable vascular stents for magnetic resonance imaging and long-term visualization.

Benefiting from their good biosafety and bioabsorbability, polymeric biodegradable stents (BDSs) have promising application prospects in the treatment of cardiovascular diseases. However, due to the low density of the polymer itself, it is difficult to visualize with medical imaging techniques such as CT and MRI, which leads to difficulties in accurate BDS localization and subsequent non-invasive evaluation. Therefore, modification of BDSs to adapt to monitoring techniques for clinical use without affecting their biocompatibility and mechanical properties is a promising strategy to support the clinical translation of BDSs. In this study, Fe3O4 superparamagnetic iron oxide nanoparticles (SPIONs) were synthesized to modify the BDS by ultrasonic spraying. Due to the T2-weighted MR imaging enhancement capability of SPIONs, the fabricated SPION-BDS can be entirely visualized and long-term monitored under MR imaging. Further, a stent degradation assessment method based on the analysis of image gray value changes was established. In conclusion, the constructed SPION-BDS provides a possible solution for precise localization of BDSs after implantation, and furthermore, opens up opportunities for long-term non-invasive monitoring of in vivo BDS degradation and multimodal imaging assessment of vascular endothelial remodeling.

Foreground segmentation and location of coal and gangue under complex similar background

To improve the foreground segmentation and location accuracy of complex coal gangue images with gray histogram distribution close to the unimodal shape, a contour detection algorithm of the grayscale fluctuation matrix is proposed. The contour and non-contour pixels of coal and gangue images are investigated, and the result indicates that the gray values of the pixels around the contour exhibit the non-uniform distribution, and the gray value changes in different directions are significantly different. Accordingly, a grayscale fluctuation matrix is built by calculating the change amplitude of pixels in different directions, and multiple features are extracted from the grayscale fluctuation matrix to realize the target contour segmentation. Furthermore, the contour is optimized using the historical and future information of the contour image, thus effectively removing numerous false contours, reproducing some hidden contours and increasing segmentation accuracy. This method has high accuracy, and the maximum error rates of the pixel area and center coordinate of contour detection are 4.404% and 3.18% respectively. This study provides a feasible solution to the edge detection and segmentation of images with similar and complex backgrounds.

The monitoring of bridge under complex illumination based on digital image technology

In the actual bridge monitoring field, the change of illumination is an urgent problem to be solved in digital image technology. At present, when using markers to measure the displacement of bridges, problems such as the change of image gray value, uneven distribution of light, and surface defects of material cause identification difficulties. In this paper, a new recognition algorithm called the dual-channel method is proposed. Based on the dark channel principle and OSTU theory, the dual-channel method can automatically select the image gray threshold, which is used to solve the recognition problem to achieve long-term monitoring. Experimental results show this method can accurately identify the markers under complex lighting conditions and greatly expand the range of gray thresholds. Compared with the traditional displacement meter, measurement errors of the dual-channel method are less than 3%. The new method can achieve real-term effective bridge monitoring, which provides a theoretical basis for practical engineering.

Light-shading reaction microfluidic PMMA/paper detection system for detection of cyclamate concentration in foods

Cyclamate is an artificial sweetener with high sweetness and low calories, and is a common sugar substitute for weight control and diabetic patients. However, excessive cyclamate consumption is associated with various health disorders, and hence it is prohibited as a food additive in many countries around the world. The current research proposes a light-shading reaction microfluidic PMMA/paper detection (MPD) system for determining the cyclamate concentration in food. In the current system, inject 10 μL of the extracted sodium cyclamate sample into the sample chamber of the MPD device, perform the diazotization reaction under shading conditions, and then suck it into the detection area through a paper strip, which consists of a paper chip embedded with modified Bratton-Marshall reagent. Once the paper chip is thoroughly wetted, the MPD device is inserted into a microanalysis box, where a fuchsia azo reaction compound is produced through heating at 40 °C for 3 min. The reaction complex is observed by a camera and the reaction image is wirelessly transmitted to a smartphone, and the concentration of sodium cyclamate is measured through the self-developed grayscale software. The results obtained for the sodium cyclamate samples with a concentration in the range of 50–1000 ppm show that the measured gray value changes linearly with the sodium cyclamate concentration, and the correlation coefficient (R2) is 0.9898. By analyzing the concentration of sodium cyclamate in 10 real-world samples, the practical feasibility of the current MPD system is proved. The results showed that the concentration measurement value did not deviate by more than 4.8 % from the value obtained using the conventional liquid chromatography/tandem mass spectrometry (LC-MS/MS) method.

X-ray micro-computed tomography in the assessment of penile cavernous fibrosis in a rabbit castration model.

Current assessment methods of penile cavernous fibrosis in animal models have limitations due to the inability to provide complex and volume analysis of fibrotic alterations. The aim was to evaluate micro-computed tomography for assessment of cavernous fibrosis and compare it with histological, histochemical, immunohistochemical, and RT-PCR analysis. A controlled trial was performed involving 25 New Zealand male rabbits with induced testosterone deficiency by orchidectomy. Penile samples were obtained before and after 7, 14, 21, and 84 days from orchidectomy. We consistently performed (a) gray value analysis of corpora cavernosa 3D models reconstructed after micro-computed tomography, (b) morphometry of smooth muscles/connective tissue ratio, collagen type I/III ratio, and area of TGF-beta-1 expression in corpora cavernosa, and (c) RT-PCR of TGF-beta-1 expression. Micro-computed tomography allowed visualization of penile structures at a resolution comparable to light microscopy. Gray values of corpora cavernosa decreased from 1673 (1512-1773) on the initial day to 1184 (1089-1232) on the 21st day (p<0.005). However, on the 84th day, it increased to 1610 (1551-1768). On 21st and 84th days, there was observed a significant decrease in smooth muscle/connective tissue ratio and a significant increase in collagen type I/III ratio (p<0.05). TGF-beta1 expression increased on the 84th day according to immunohistochemistry (p<0.005). RT-PCR was impossible to conduct due to the absence of RNA in obtained samples after micro-CT. Micro-computed tomography provided 3D visualization of entire corpora cavernosa and assessment of radiodensity alterations by gray value analysis in fibrosis progression. We speculate that gray value changes at early and late fibrosis stages could be related to tissue reorganization. RT-PCR is impossible to conduct on tissue samples studied by micro-CT due to RNA destruction. We also suggest that micro-computed tomography could negatively affect the immunohistochemical outcome, as a significant increase of TGF-beta-1 expression occurs later than histological fibrotic signs.

Visualization of mercury percolation in porous hardened cement paste by means of X-ray computed tomography

Mercury intrusion porosimetry (MIP) has been extensively used for the pore structure characterization of porous materials, but the percolation of mercury in porous cement-based materials during MIP has never been comprehensively investigated before. Here we visually probe the mercury percolation in a porous hardened cement paste (HCP) using X-ray computed tomography (X-CT). Novel double surface coatings on the HCP samples before and after MIP tests by an epoxy resin are specifically designed. The first coating enables the one-directional penetration of mercury in the HCP samples during MIP, while the second coating can partially seal the release of the entrapped mercury. MIP tests are operated under different maximum applied pressures (10,000 and 30,000 psi) and equilibrium time (5, 10, and 30 s). The high X-ray attenuation of mercury enables the visual trace of the intrusion mercury percolation pathways and the entrapped mercury clusters in the HCP samples by X-CT. The position-dependent entrapped mercury clusters in the pores account for the gray value changes and gradients in the HCP samples after MIP. The MIP characteristics, such as, total intrusion volume, volume size distribution and mercury entrapment, change with the maximum applied pressure and equilibrium time, but the percolation pore size shows the consistent values. The findings of this work deepen the understandings of MIP for the microstructure characterization of porous materials.

RETRACTED ARTICLE: Dynamic identification of coastal climate characteristics and traditional residential space design based on multi-source remote sensing images

In this article, the author gives a detailed introduction to the establishment of the target feature database of the multi-source remote sensing image area. When building the target feature database, the target must be extracted first. There are many studies in this area, so the author focuses on how to extract high-resolution image targets and introduces the types of target features and how to extract common target features. Nowadays, the research of multi-source remote sensing technology has made significant progress, and people have begun to invest in the research of remote sensing image atmospheric climate correction methods. The sensor will obtain more imaging information, but not all of this information comes from the target features. In addition, the information obtained is also affected by atmospheric molecules, and the contrast is greatly reduced. The data obtained in this way is not even after processing able to achieve the target accuracy. In order to solve the problem of the decrease of matching degree due to the nonlinear change of gray value, the author proposes a new feature point matching algorithm, which uses spectral information when fitting remote sensing image bands. With the development of economy, people have new requirements for the living environment. When designing space, designers should pay more attention to the sense of experience. In this article, the author analyzes the space design of traditional houses. When designing traditional dwellings, it is often necessary to combine local traditional dwelling resources to create a better experience for customers, so that traditional dwelling resources can give full play to their functions, expand influence and open up visibility while meeting consumer needs, promote the development of the local tourism industry, and bring economic benefits to the local area.

Signature Handwriting Examination Based on Photometric Stereo Imaging and Change of Gray Value

Signature Handwriting Examination Based on Photometric Stereo Imaging and Change of Gray Value

Avaliação dos valores médios de cinza em um gato com insuficiência renal crônica: relato de caso

ABSTRACT In this case, a 12-year-old female domestic cat with chronic renal failure (CRF), which had lived longer than the mean survival time for cats with that condition, was monitored to evaluate the effects of treatment and mean gray value (MGV) changes. The cat has lived for nearly four years since the diagnosis. Probiotics have been used as an additional, classical supportive therapy since the beginning of treatment. The temporal changes in renal MGV were statistically evaluated in the last year of the four-year period. The cat had a comfortable existence and good body condition all her life and probiotic therapy may have had a positive influence post-CRF diagnosis. Ultrasonography (US) examination is a commonly used tool for monitoring the CRF situation, but it is not particularly sensitive. Therefore, MGV may be more useful for the quantitative evaluation of the extent of renal failure. Also, to the best of our knowledge, this is the first report for a long-term clinical evaluation of MGV in a cat with CRF. The aim of this case report was the evaluation of the relationship between MGV and clinical and biochemical changes in a cat with chronic renal failure.

Scarf Defect Detection Method Based on Periodicity of Braided Texture

The pure color scarf image is a typical periodic texture image. Based on the periodicity of scarf image texture, in order to eliminate the influence of periodical change of gray value of scarf image on scarf defect detection caused by periodic texture change, a defect detection method based on scarf knitting texture periodicity is proposed. Firstly, autocorrelation function is applied to determine the texture period of the averaged image, and the texture period is taken as the parameter to improve the quality of scarf defect detection Row down sampling and bilinear interpolation are used to eliminate the periodic change of gray value caused by texture. After that, the method based on maximum inter class variance is used to cut the image to complete the defect detection of scarf image. Through a large number of experiments, it is proved that this method has good effect on scarf defect detection, and has the characteristics of stable effect and strong practicability.

Facial alveolar bone alterations and gray value changes based on cone beam computed tomography around maxillary anterior implants: A clinical retrospective study of 1-3years.

The purpose of this cone beam computed tomography (CBCT) study was to describe facial alveolar bone alterations and gray value (GV) changes around implants in aesthetic anterior maxilla with simultaneous guided bone regeneration (GBR) and to investigate potential influence of factors related to vertical alveolar bone stability, such as particle sizes of the deproteinized bovine bone mineral (DBBM) used. A retrospective study design was adopted. Four facio-palatal cross-sectional CBCT images of 166 implants from 124 patients who had maxillary anterior implants were obtained. Measurements of the vertical facial alveolar bone level (VFBL), horizontal facial alveolar bone thickness (HFBT), and GV were identified of 1-3years. Then, correlation coefficients for those parameters were calculated. Finally, linear mixed models were established to investigate potential factors influencing vertical alveolar bone resorption. Facial alveolar bone underwent fast bone modeling and remodeling during the first 6months, with decreases of 1.00±1.19 and 0.74±0.86mm in VFBL and HFBT in implant shoulder, respectively, and there was positive and significant correlation between the alterations in VFBL and HFBT1 (rs =.516, p=.000). Linear mixed models identified particle size of DBBM as a critical factor associated with vertical bone resorption (p=.000). The GV gradually increased during the follow-up period. Rapid and unavoidable peri-implant bone resorption usually happened during the first 6months after implant placement. GBR is a predictable treatment for maxillary anterior implants, since GV has an increasing trend. Large bone particles of DBBM help maintain vertical alveolar bone stability.

Edge detection in noisy images with different edge types

Edge Detection in an image is a process that produces edges of image objects, the purpose of which is to mark the parts that become detailed images to improve the details of blurry images, which occur due to the effects of the image acquisition process. Edge is defined as a change in the intensity of a large distance. Based on changes in intensity, there are three types of edges in digital images, namely, step edges, ramps edge, and noisy edge. On step edges where the intensity or gray value changes very fast The Gradient Method is able to detect better. On the ramp edge where the gray value slowly changes the Laplace method is able to detect better than the Gradient Method. On a noisy edge, the existence of noise in the image can bring up the other edges around the actual edge and can also shift the actual edge position. In this study, the authors conducted edge detection in the image by means of determining the right edge detection method to detect edges in noisy images. Noise is obtained by generating a Gaussian Noise in the image. The results showed that, without filtering the image, in noisy edge, the LoG operator was able to detect edges and reduce noise better than Canny. However, by selecting the right threshold that matches the σ (standard deviation), Canny also capable to provide good edge detection results.

Effect of Bifidobacterium-induced changes in tumor tissue acoustic properties on efficacy of high-intensity focused ultrasound ablation

To investigate the effects of Bifidobacterium on the acoustic characteristics of tumor tissue and how such acoustic changes affect the efficacy of high-intensity focused ultrasound (HIFU) ablation in nude mice. Forty mice bearing human breast cancer cell (MDA-MB-231) xenograft were randomized into experimental group (n=20) and control group (n=20) for intravenous injection of Bifidobacterium suspension (200 μL, 4 × 108 cfu/mL) and PBS (200 μL) for 3 consecutive days, respectively. Before and at 3 and 7 days after the first injection, shear wave elastography was used to evaluate the hardness of the tumor tissue. On day 7 after the first injection, 10 mice from each group were sacrificed and the sound velocity and sound attenuation of the tumor tissues were measured. The changes in the collagen fibers in the tumors were evaluated using Masson staining, and neovascularization in the tumor was assessed with immunohistochemistry for platelet endothelial cell adhesion molecule-1 (PECAM-1/CD31). The remaining 10 tumor-bearing mice in each group were subjected to HIFU ablation, and the ablation efficiency was evaluated by assessing the changes in irradiation gray values, coagulative necrosis volume, energy efficiency factor (EEF) and irradiation area and by pathological examination with HE staining. In the experimental group, the collagen fibers in the tumor tissues were strong and densely aligned, and the tumors contained fewer new blood vessels showing strip-or spot-like morphologies. In the control group, the collagen fibers in the tumors were thin and loosely arranged, and the tumors showed abundant elongated or round new blood vessels. Bifidobacterium colonized in the tumor 7 days after the injection, and the tumor hardness was significantly greater in the experimental group than in the control group (P=0.01); the acoustic velocity (P=0.001) and the acoustic attenuation (P=0.000) of the tumor tissues were also greater in the experimental group. HIFU irradiation resulted in significantly greater changes in the gray scale of tumor (P=0.0006) and larger coagulative necrosis volume (P=0.0045) in the experimental group than in the control group, and the EEF was significantly smaller in the experimental group (P=0.0134). Bifidobacterium can cause changes in collagen fiber content, acoustic velocity and attenuation in the tumor tissue and reduce the EEF of HIFU irradiation, thereby improving the efficacy of HIFU irradiation.

Analysis of micro-structural damage evolution of concrete through coupled X-ray computed tomography and gray-level co-occurrence matrices method

Concrete CT test is an effective method used to analyze micro-structural damage evolution of concrete under loading condition. In the CT images of different stress states in the same section, gray value changes in the original number matrix of CT image are the key to investigate microscopic damage evolution of concrete. However, the slight changes in the gray value of CT images before peak stress cannot be intuitively observed with the naked eye. This study mainly aims to develop a coupled method based on statistical method and X-ray CT to extract indicators of such subtle changes. Different cross-sectional CT images of concrete at different stress stages were obtained by uniaxial static compression CT test. The theory of the grey level co-occurrence matrices (GLCM) was then adopted to analyze micro-damage evolution and crack properties. That is, the GLCM of the CT images were calculated, and four statistical features including contrast, energy, correlation, and homogeneity were extracted, which can be extended into quantitative analysis of micro-damage hidden in the CT images of concrete. Results exhibited that the damage growth area, concentrating between the 45th and 225th concrete cross-section, could be predicted by the distribution of four statistical features (i.e., contrast, energy, correlation and homogeneity) at the fourth scan, and it is consistent with the crack location in the fifth scan. The contrast, energy and homogeneity follow the Gaussian distribution under five scan stages, and the correlation follows the Laplace distribution. In addition, the changes of bandwidth in color heat map illustrating the GLCM before and after specimen failure show that the bandwidth is positively correlated with micro-structural damage of concrete specimen.

Applying Speckle Noise Suppression to Refractive Indices Change Detection in Porous Silicon Microarrays.

The gray value method can be used to detect gray value changes of each unit almost parallel to the surface image of PSi (porous silicon) microarrays and indirectly measure the refractive index changes of each unit. However, the speckles of different noise intensities produced by lasers on a porous silicon surface have different effects on the gray value of the measured image. This results in inaccurate results of refractive index changes obtained from the change in gray value. Therefore, it is very important to reduce the influence of speckle noise on measurement results. In this paper, a new algorithm based on the concepts of probability-based nonlocal-means filtering (PNLM), gradient operator, and median filtering is proposed for gray value restoration of porous silicon microarray images. A good linear relationship between gray value change and refractive index change is obtained, which can reduce the influence of speckle noise on the gray value of the PSi microarray image, improving detection accuracy. This means the method based on gray value change detection can be applied to the biological detection of PSi microarray arrays.

Change Detection Based on Multi-Grained Cascade Forest and Multi-Scale Fusion for SAR Images

In this paper, a novel change detection approach based on multi-grained cascade forest (gcForest) and multi-scale fusion for synthetic aperture radar (SAR) images is proposed. It detects the changed and unchanged areas of the images by using the well-trained gcForest. Most existing change detection methods need to select the appropriate size of the image block. However, the single size image block only provides a part of the local information, and gcForest cannot achieve a good effect on the image representation learning ability. Therefore, the proposed approach chooses different sizes of image blocks as the input of gcForest, which can learn more image characteristics and reduce the influence of the local information of the image on the classification result as well. In addition, in order to improve the detection accuracy of those pixels whose gray value changes abruptly, the proposed approach combines gradient information of the difference image with the probability map obtained from the well-trained gcForest. Therefore, the image edge information can be enhanced and the accuracy of edge detection can be improved by extracting the image gradient information. Experiments on four data sets indicate that the proposed approach outperforms other state-of-the-art algorithms.

Progressive Decline in Gray and White Matter Integrity in de novo Parkinson's Disease: An Analysis of Longitudinal Parkinson Progression Markers Initiative Diffusion Tensor Imaging Data.

Background: Progressive neuronal loss in neurodegenerative diseases such as Parkinson’s disease (PD) is associated with progressive degeneration of associated white matter tracts as measured by diffusion tensor imaging (DTI). These findings may have diagnostic and functional implications but their value in de novo PD remains unknown. Here we analyzed longitudinal DTI data from Parkinson’s Progression Markers Initiative de novo PD patients for changes over time relative to healthy control (HC) participants.Methods: Baseline and 1-year follow-up DTI MRI data from 71 PD patients and 45 HC PPMI participants were included in the analyses. Whole-brain fractional anisotropy (FA) and mean diffusivity (MD) images were compared for baseline group differences and group–by–time interactions. Baseline and 1-year changes in DTI values were correlated with changes in DTI measures and symptom severity, respectively.Results: At baseline, PD patients showed significantly increased FA in brainstem, cerebellar, anterior corpus callosal, inferior frontal and inferior fronto-occipital white matter and increased MD in primary sensorimotor and supplementary motor regions. Over 1 year PD patients showed a significantly stronger decline in FA compared to HC in the optic radiation and corpus callosum and parietal, occipital, posterior temporal, posterior thalamic, and vermis gray matter. Significant increases in MD were observed in white matter of the midbrain, optic radiation and corpus callosum, while gray matter of prefrontal, insular and posterior thalamic regions. Baseline brainstem FA white matter (WM) values predicted 1-year changes in FA white matter and MD gray matter values. White but not gray matter changes in both FA and MD were significantly associated with changes in symptom severity.Conclusion: Significant gray and white matter DTI alterations are observable at the time of PD diagnosis and expand in the first year of de novo PD to other cortical and white matter regions. This pattern of DTI changes is in line with preclinical and neuroanatomical studies suggesting that the increased spatial spread of alpha-synuclein neuropathology is the key mechanism of PD progression. Taken together, these findings suggest that DTI may serve as a sensitive biomarker of disease progression in early-stage PD.

Application of RNAMlet to surface defect identification of steels

As three main production lines of steels, continuous casting slabs, hot rolled steel plates and cold rolled steel strips have different surface appearances and are produced at different speeds of their production lines. Therefore, the algorithms for the surface defect identifications of the three steel products have different requirements for real-time and anti-interference. The existing algorithms cannot be adaptively applied to surface defect identification of the three steel products. A new method of adaptive multi-scale geometric analysis named RNAMlet was proposed. The idea of RNAMlet came from the non-symmetry anti-packing pattern representation model (NAM). The image is decomposed into a set of rectangular blocks asymmetrically according to gray value changes of image pixels. Then two-dimensional Haar wavelet transform is applied to all blocks. If the image background is complex, the number of blocks is large, and more details of the image are utilized. If the image background is simple, the number of blocks is small, and less computation time is needed. RNAMlet was tested with image samples of the three steel products, and compared with three classical methods of multi-scale geometric analysis, including Contourlet, Shearlet and Tetrolet. For the image samples with complicated backgrounds, such as continuous casting slabs and hot rolled steel plates, the defect identification rate obtained by RNAMlet was 1% higher than other three methods. For the image samples with simple backgrounds, such as cold rolled steel strips, the computation time of RNAMlet was one-tenth of the other three MGA methods, while the defect identification rates obtained by RNAMlet were higher than the other three methods.