The importance of the accuracy of preparing biological specimen as histological sections that can be examined under a microscope lies in reflecting a true image of the tissue that includes all its components, which ar...The importance of the accuracy of preparing biological specimen as histological sections that can be examined under a microscope lies in reflecting a true image of the tissue that includes all its components, which are used in scientific research or for the purpose of diagnosing various diseases of the body. Despite this, some cellular structures within the tissue may suffer from some alterations that result from the appearance of defects during any stage of preparing these microscopic sections, which alter or interfere with the precise cellular structures and morphology that constitute the tissue and thus give a different image for tissue features and cause confusion in the work histopathologist in the diagnosis. There are several reasons that can cause a misdiagnosis of the sample that occurs during the surgical separation process or after separation during the stages of microscopic preparation techniques from fixation stage, tissue processing, embedding or microtomy, staining until mounting procedures. The constant need to identify these defects and their causes in addition to try to reduce them is one of the biggest challenges evident in pathology laboratories. Therefore, this study aims to review the most common defects that occur in any stage of tissue processing, with an explanation of their causes and appropriate ways to avoid them.展开更多
Limited by the dynamic range of the detector,saturation artifacts usually occur in optical coherence tomography(OCT)imaging for high scattering media.The available methods are difficult to remove saturation artifacts ...Limited by the dynamic range of the detector,saturation artifacts usually occur in optical coherence tomography(OCT)imaging for high scattering media.The available methods are difficult to remove saturation artifacts and restore texture completely in OCT images.We proposed a deep learning-based inpainting method of saturation artifacts in this paper.The generation mechanism of saturation artifacts was analyzed,and experimental and simulated datasets were built based on the mechanism.Enhanced super-resolution generative adversarial networks were trained by the clear–saturated phantom image pairs.The perfect reconstructed results of experimental zebrafish and thyroid OCT images proved its feasibility,strong generalization,and robustness.展开更多
This study addresses challenges in fetal magnetic resonance imaging (MRI) related to motion artifacts, maternal respiration, and hardware limitations. To enhance MRI quality, we employ deep learning techniques, specif...This study addresses challenges in fetal magnetic resonance imaging (MRI) related to motion artifacts, maternal respiration, and hardware limitations. To enhance MRI quality, we employ deep learning techniques, specifically utilizing Cycle GAN. Synthetic pairs of images, simulating artifacts in fetal MRI, are generated to train the model. Our primary contribution is the use of Cycle GAN for fetal MRI restoration, augmented by artificially corrupted data. We compare three approaches (supervised Cycle GAN, Pix2Pix, and Mobile Unet) for artifact removal. Experimental results demonstrate that the proposed supervised Cycle GAN effectively removes artifacts while preserving image details, as validated through Structural Similarity Index Measure (SSIM) and normalized Mean Absolute Error (MAE). The method proves comparable to alternatives but avoids the generation of spurious regions, which is crucial for medical accuracy.展开更多
BACKGROUND Artifacts are common when using two-dimensional shear wave elastography(2-D SWE)to measure liver stiffness(LS),but they are poorly recognized.AIM To investigate the presence and influence of artifacts in 2-...BACKGROUND Artifacts are common when using two-dimensional shear wave elastography(2-D SWE)to measure liver stiffness(LS),but they are poorly recognized.AIM To investigate the presence and influence of artifacts in 2-D SWE of liver.METHODS We included 158 patients with chronic liver disease,who underwent 2-D SWE examination by a novice and an expert.A cross line at the center of the elastogram was drawn and was divided it into four locations:top-left,top-right,bottom-left,and bottom-right.The occurrence frequency of artifacts in different locations was compared.The influence of artifacts on the LS measurements was evaluated by comparing the elastogram with the most artifacts(EMA)and the elastogram with the least artifacts(ELA).RESULTS The percentage of elastograms with artifacts in the novice(51.7%)was significantly higher than that of the expert(19.6%)(P<0.001).It was found that both operators had the highest frequency of artifacts at bottom-left,followed by top-left and bottom-right,and top-right had the lowest frequency.The LS values(LSVs)and standard deviation values of EMAs were significantly higher than those of ELAs for both operators.An intraclass correlation coefficient value of 0.96 was found in the LSVs of EMAs of the two operators,and it increased to 0.98 when the LSVs of the ELAs were used.Both operators had lower stability index values for EMAs than ELAs,but the difference was only statistically significant for the novice.CONCLUSION Artifacts are common when using 2-D SWE to measure LS,especially for the novice.Artifacts may lead to the overestimation of LS and reduce the repeatability and reliability of LS measurements.展开更多
X-ray dark-field imaging using a grating interferometer has shown potential benefits for a variety of applications in recent years.X-ray dark-field image is commonly retrieved by using discrete Fourier transform from ...X-ray dark-field imaging using a grating interferometer has shown potential benefits for a variety of applications in recent years.X-ray dark-field image is commonly retrieved by using discrete Fourier transform from the acquired phasestepping data.The retrieval process assumes a constant phase step size and a constant flux for each stepped grating position.However,stepping errors and flux fluctuations inevitably occur due to external vibrations and/or thermal drift during data acquisition.Previous studies have shown that those influences introduce errors in the acquired phase-stepping data,which cause obvious moiréartifacts in the retrieved refraction image.This work investigates moiréartifacts in x-ray dark-field imaging as a result of flux fluctuations.For the retrieved mean intensity,amplitude,visibility and dark-field images,the dependence of moiréartifacts on flux fluctuation factors is theoretically derived respectively by using a first-order Taylor series expansion.Results of synchrotron radiation experiments verify the validity of the derived analytical formulas.The spatial frequency characteristics of moiréartifacts are analyzed and compared to those induced by phase-stepping errors.It illustrates that moiréartifacts can be estimated by a weighted mean of flux fluctuation factors,with the weighting factors dependent on the moiréphase and different greatly for each retrieved image.Furthermore,moiréartifacts can even be affected by object’s features not displayed in the particular contrast.These results can be used to interpret images correctly,identify sources of moiréartifacts,and develop dedicated algorithms to remove moiréartifacts in the retrieved multi-contrast images.展开更多
目的观察运动伪影校正技术(MFT)对于改善肾动脉瘤锥形束CT(CBCT)图像质量的价值。方法前瞻性选取20例拟接受经导管动脉栓塞治疗的肾动脉瘤患者,于CBCT引导下行肾动脉造影,采用MFT处理运动伪影;对MFT校正前、后图像质量进行主、客观评价...目的观察运动伪影校正技术(MFT)对于改善肾动脉瘤锥形束CT(CBCT)图像质量的价值。方法前瞻性选取20例拟接受经导管动脉栓塞治疗的肾动脉瘤患者,于CBCT引导下行肾动脉造影,采用MFT处理运动伪影;对MFT校正前、后图像质量进行主、客观评价,评估其显示肾动脉、载瘤动脉及靶区血管树情况,测算单位密度像素平均值(mean)、标准差(SD)及血管边缘锐化误差率。结果MFT校正后,肾动脉瘤最大密度投影图像显示肾动脉、重建CBCT图像显示载瘤动脉均明显优于校正前(P均<0.05);利用Flightplan for Liver软件可自动提取清晰的血管树;肾动脉瘤CBCT图像SD及血管边缘锐化误差率明显减小而mean明显增加(P均<0.05)。结论MFT可有效改善肾动脉瘤CBCT图像质量。展开更多
文摘The importance of the accuracy of preparing biological specimen as histological sections that can be examined under a microscope lies in reflecting a true image of the tissue that includes all its components, which are used in scientific research or for the purpose of diagnosing various diseases of the body. Despite this, some cellular structures within the tissue may suffer from some alterations that result from the appearance of defects during any stage of preparing these microscopic sections, which alter or interfere with the precise cellular structures and morphology that constitute the tissue and thus give a different image for tissue features and cause confusion in the work histopathologist in the diagnosis. There are several reasons that can cause a misdiagnosis of the sample that occurs during the surgical separation process or after separation during the stages of microscopic preparation techniques from fixation stage, tissue processing, embedding or microtomy, staining until mounting procedures. The constant need to identify these defects and their causes in addition to try to reduce them is one of the biggest challenges evident in pathology laboratories. Therefore, this study aims to review the most common defects that occur in any stage of tissue processing, with an explanation of their causes and appropriate ways to avoid them.
基金supported by the National Natural Science Foundation of China(62375144 and 61875092)Tianjin Foundation of Natural Science(21JCYBJC00260)Beijing-Tianjin-Hebei Basic Research Cooperation Special Program(19JCZDJC65300).
文摘Limited by the dynamic range of the detector,saturation artifacts usually occur in optical coherence tomography(OCT)imaging for high scattering media.The available methods are difficult to remove saturation artifacts and restore texture completely in OCT images.We proposed a deep learning-based inpainting method of saturation artifacts in this paper.The generation mechanism of saturation artifacts was analyzed,and experimental and simulated datasets were built based on the mechanism.Enhanced super-resolution generative adversarial networks were trained by the clear–saturated phantom image pairs.The perfect reconstructed results of experimental zebrafish and thyroid OCT images proved its feasibility,strong generalization,and robustness.
文摘This study addresses challenges in fetal magnetic resonance imaging (MRI) related to motion artifacts, maternal respiration, and hardware limitations. To enhance MRI quality, we employ deep learning techniques, specifically utilizing Cycle GAN. Synthetic pairs of images, simulating artifacts in fetal MRI, are generated to train the model. Our primary contribution is the use of Cycle GAN for fetal MRI restoration, augmented by artificially corrupted data. We compare three approaches (supervised Cycle GAN, Pix2Pix, and Mobile Unet) for artifact removal. Experimental results demonstrate that the proposed supervised Cycle GAN effectively removes artifacts while preserving image details, as validated through Structural Similarity Index Measure (SSIM) and normalized Mean Absolute Error (MAE). The method proves comparable to alternatives but avoids the generation of spurious regions, which is crucial for medical accuracy.
文摘BACKGROUND Artifacts are common when using two-dimensional shear wave elastography(2-D SWE)to measure liver stiffness(LS),but they are poorly recognized.AIM To investigate the presence and influence of artifacts in 2-D SWE of liver.METHODS We included 158 patients with chronic liver disease,who underwent 2-D SWE examination by a novice and an expert.A cross line at the center of the elastogram was drawn and was divided it into four locations:top-left,top-right,bottom-left,and bottom-right.The occurrence frequency of artifacts in different locations was compared.The influence of artifacts on the LS measurements was evaluated by comparing the elastogram with the most artifacts(EMA)and the elastogram with the least artifacts(ELA).RESULTS The percentage of elastograms with artifacts in the novice(51.7%)was significantly higher than that of the expert(19.6%)(P<0.001).It was found that both operators had the highest frequency of artifacts at bottom-left,followed by top-left and bottom-right,and top-right had the lowest frequency.The LS values(LSVs)and standard deviation values of EMAs were significantly higher than those of ELAs for both operators.An intraclass correlation coefficient value of 0.96 was found in the LSVs of EMAs of the two operators,and it increased to 0.98 when the LSVs of the ELAs were used.Both operators had lower stability index values for EMAs than ELAs,but the difference was only statistically significant for the novice.CONCLUSION Artifacts are common when using 2-D SWE to measure LS,especially for the novice.Artifacts may lead to the overestimation of LS and reduce the repeatability and reliability of LS measurements.
基金the Natural Science Foundation of China(Grant Nos.U1532113,11475170,and 11905041)Fundamental Research Funds for the Central Universities(Grant No.PA2020GDKC0024)Anhui Provincial Natural Science Foundation(Grant No.2208085MA18).
文摘X-ray dark-field imaging using a grating interferometer has shown potential benefits for a variety of applications in recent years.X-ray dark-field image is commonly retrieved by using discrete Fourier transform from the acquired phasestepping data.The retrieval process assumes a constant phase step size and a constant flux for each stepped grating position.However,stepping errors and flux fluctuations inevitably occur due to external vibrations and/or thermal drift during data acquisition.Previous studies have shown that those influences introduce errors in the acquired phase-stepping data,which cause obvious moiréartifacts in the retrieved refraction image.This work investigates moiréartifacts in x-ray dark-field imaging as a result of flux fluctuations.For the retrieved mean intensity,amplitude,visibility and dark-field images,the dependence of moiréartifacts on flux fluctuation factors is theoretically derived respectively by using a first-order Taylor series expansion.Results of synchrotron radiation experiments verify the validity of the derived analytical formulas.The spatial frequency characteristics of moiréartifacts are analyzed and compared to those induced by phase-stepping errors.It illustrates that moiréartifacts can be estimated by a weighted mean of flux fluctuation factors,with the weighting factors dependent on the moiréphase and different greatly for each retrieved image.Furthermore,moiréartifacts can even be affected by object’s features not displayed in the particular contrast.These results can be used to interpret images correctly,identify sources of moiréartifacts,and develop dedicated algorithms to remove moiréartifacts in the retrieved multi-contrast images.
文摘目的观察运动伪影校正技术(MFT)对于改善肾动脉瘤锥形束CT(CBCT)图像质量的价值。方法前瞻性选取20例拟接受经导管动脉栓塞治疗的肾动脉瘤患者,于CBCT引导下行肾动脉造影,采用MFT处理运动伪影;对MFT校正前、后图像质量进行主、客观评价,评估其显示肾动脉、载瘤动脉及靶区血管树情况,测算单位密度像素平均值(mean)、标准差(SD)及血管边缘锐化误差率。结果MFT校正后,肾动脉瘤最大密度投影图像显示肾动脉、重建CBCT图像显示载瘤动脉均明显优于校正前(P均<0.05);利用Flightplan for Liver软件可自动提取清晰的血管树;肾动脉瘤CBCT图像SD及血管边缘锐化误差率明显减小而mean明显增加(P均<0.05)。结论MFT可有效改善肾动脉瘤CBCT图像质量。
