scholarly journals Deep-Learning-Based Color Doppler Ultrasound Image Feature in the Diagnosis of Elderly Patients with Chronic Heart Failure Complicated with Sarcopenia

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Peng Bian ◽  
Xiyu Zhang ◽  
Ruihong Liu ◽  
Huijie Li ◽  
Qingqing Zhang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Doppler Ultrasound ◽  
Color Doppler ◽  
Ultrasound Image ◽  
Color Doppler Ultrasound ◽  
Control Group ◽  
Learning Technology ◽  
Ultrasound Images ◽  
Before And After ◽  
Experimental Group

The neural network algorithm of deep learning was applied to optimize and improve color Doppler ultrasound images, which was used for the research on elderly patients with chronic heart failure (CHF) complicated with sarcopenia, so as to analyze the effect of the deep-learning-based color Doppler ultrasound image on the diagnosis of CHF. 259 patients were selected randomly in this study, who were admitted to hospital from October 2017 to March 2020 and were diagnosed with sarcopenia. Then, all of them underwent cardiac ultrasound examination and were divided into two groups according to whether deep learning technology was used for image processing or not. A group of routine unprocessed images was set as the control group, and the images processed by deep learning were set as the experimental group. The results of color Doppler images before and after processing were analyzed and compared; that is, the processed images of the experimental group were clearer and had higher resolution than the unprocessed images of the control group, with the peak signal-to-noise ratio (PSNR) = 20 and structural similarity index measure (SSIM) = 0.09; the similarity between the final diagnosis results and the examination results of the experimental group (93.5%) was higher than that of the control group (87.0%), and the comparison was statistically significant ( P < 0.05 ); among all the patients diagnosed with sarcopenia, 88.9% were also eventually diagnosed with CHF and only a small part of them were diagnosed with other diseases, with statistical significance ( P < 0.05 ). In conclusion, deep learning technology had certain application value in processing color Doppler ultrasound images. Although there was no obvious difference between the color Doppler ultrasound images before and after processing, they could all make a better diagnosis. Moreover, the research results showed the correlation between CHF and sarcopenia.

scholarly journals Diagnostic Value of Color Doppler Ultrasound Combined with Superb Microvascular Imaging in the Detection of Small Renal Tumors Less than 3 cm Treated with Jinkui Shenqi Pills

2021 ◽  
Vol 2021 ◽  
pp. 1-5
Author(s):  
Yuping Gong ◽  
Shuhui Li
Keyword(s):  
Doppler Ultrasound ◽  
Color Doppler ◽  
Statistical Significance ◽  
Color Doppler Ultrasound ◽  
Diagnostic Value ◽  
Renal Tumors ◽  
Control Group ◽  
Detection Accuracy ◽  
Experimental Group ◽  
Negative Detection

The purpose of this study was to investigate the diagnostic value of color Doppler ultrasound combined with superb microvascular imaging (SMI) in the detection of small renal tumors less than 3 cm treated with Jinkui Shenqi pills. 50 cases were randomly selected from the patients with angioleiomyoma (a kind of small renal tumor) less than 3 cm confirmed by pathological examination and treated in our hospital from January 2018 to January 2020. All patients were treated with Jinkui Shenqi pills. All patients were first detected by color Doppler ultrasound and then by SMI. The results of color Doppler ultrasound were used as the control group, while those of color Doppler ultrasound combined with SMI were used as the experimental group. After that, the specificity, sensitivity, positive and negative detection results, and detection accuracy were compared between the two groups. The specificity and sensitivity in the experimental group were significantly higher than those in the control group, with statistical significance ( P < 0.05 ). The cases of positive and negative detection results in the experimental group were significantly higher than those in the control group, with statistical significance ( P < 0.05 ). The detection accuracy in the experimental group was significantly higher than that in the control group, with statistical significance ( P < 0.05 ). The specificity, sensitivity, positive and negative detection results, and detection accuracy of color Doppler ultrasound combined with SMI in the detection of small renal tumors less than 3 cm treated with Jinkui Shenqi pills were all significantly higher than those of color Doppler ultrasound; therefore, the application of color Doppler ultrasound combined with SMI for the diagnosis of small renal tumors is of high value.

Development of Color Doppler Ultrasound Image-Text Management System

2014 ◽  
Vol 539 ◽  
pp. 395-399
Author(s):  
Hong Yan Jiang
Keyword(s):  
Doppler Ultrasound ◽  
Management System ◽  
Color Doppler ◽  
Ultrasound Image ◽  
Color Doppler Ultrasound ◽  
Ultrasound Images ◽  
Video Signals ◽  
Advantages And Disadvantages ◽  
System A ◽  
Image Management System

In this paper, the advantages and disadvantages of the existing ultrasonic image management system are analyzed, and also a multi-functional color Doppler ultrasound image-text management system is researched and developed in combination with the experience of color Doppler ultrasound doctors. With this system, the related operations such as color Doppler ultrasound images acquisition, processing, preservation, and medical records are implemented. In the design of the system, a professional acquisition card is used for implementing the acquisition of ordinary video signals. In the meantime, DICOM interface is designed using DICOM3.0 protocol for implementing multi-mode acquisition.

scholarly journals Prediction and Value of Ultrasound Image in Diagnosis of Fetal Central Nervous System Malformation under Deep Learning Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yuehong Zhou
Keyword(s):  
Neural Network ◽  
Central Nervous System ◽  
Nervous System ◽  
Deep Learning ◽  
Ultrasound Examination ◽  
Ultrasound Image ◽  
Control Group ◽  
Test Results ◽  
Experimental Group ◽  
Central Nervous System Malformation

This study was to explore the application of deep learning neural network (DLNN) algorithms to identify and optimize the ultrasound image so as to analyze the effect and value in diagnosis of fetal central nervous system malformation (CNSM). 63 pregnant women who were gated in the hospital were suspected of being fetal CNSM and were selected as the research objects. The ultrasound images were reserved in duplicate, and one group was defined as the control group without any processing, and images in the experimental group were processed with the convolutional neural network (CNN) algorithm to identify and optimize. The ultrasound examination results and the pathological test results before, during, and after the pregnancy were observed and compared. The results showed that the test results in the experimental group were closer to the postpartum ultrasound and the results of the pathological result, but the results in both groups showed no statistical difference in contrast to the postpartum results in terms of similarity ( P > 0.05 ). In the same pregnancy stage, the ultrasound examination results of the experimental group were higher than those in the control group, and the contrast was statistically significant ( P < 0.05 ); in the different pregnancy stages, the ultrasound examination results in the second trimester were more close to the postpartum examination results, showing statistically obvious difference ( P < 0.05 ). In conclusion, ultrasonic image based on deep learning was higher in CNSM inspection; and ultrasonic technology had to be improved for the examination in different pregnancy stages, and the accuracy of the examination results is improved. However, the amount of data in this study was too small, so the representative was not high enough, which would be improved.

scholarly journals Effect of Magnesium Sulfate on Doppler Parameters of Fetal Umbilical and Middle Cerebral Arteries in Women with Severe Preeclampsia

2012 ◽  
Vol 2 ◽  
pp. 85 ◽  
Author(s):  
Nazanin Farshchian ◽  
Negin Rezavand ◽  
Saeed Mohammadi
Keyword(s):  
Magnesium Sulfate ◽  
Doppler Ultrasound ◽  
Color Doppler ◽  
Cerebral Arteries ◽  
Color Doppler Ultrasound ◽  
Severe Preeclampsia ◽  
Resistivity Index ◽  
Middle Cerebral Arteries ◽  
Before And After ◽  
The Mean

Objective: To assess the effect of injecting magnesium sulfate on Doppler parameters of fetal umbilical and middle cerebral arteries (MCA) in women with severe preeclampsia. Materials and Methods: A total of 21 patients with severe preeclampsia admitted to Imam Reza Hospital, Kermanshah (Iran), were evaluated. Before and after administration of magnesium sulfate, Doppler ultrasound scan was carried out to measure fetal middle cerebral artery and umbilical artery blood flow. Paired t-test was used for statistical analysis. Results: After injection of magnesium sulfate, the mean resistivity index (RI)-umbilical, and pulsatility index (PI)-cerebral showed a statistically significant reduction (P < 0.001). The cerebroumbilical C/U ratio increased after the intervention (P < 0.001). The PI-umbilical (P = 0.1) and pre- and post-RI-cerebral (P = 0.96) did not have statistically significant changes. Conclusions: Infusion of magnesium sulfate significantly decreases the flow in the fetus RI-umbilical and PI-MCA, and it increases C/U ratio indices in color Doppler ultrasound.

scholarly journals Color doppler ultrasound images and their types in liver tumors.

Kanzo ◽  
1989 ◽  
Vol 30 (11) ◽  
pp. 1637-1638 ◽  
Author(s):  
Yousuke ARITA ◽  
Kazuaki YASUHARA ◽  
Jyunji FURUSE ◽  
Shoichi MATSUTANI ◽  
Masaaki EBARA ◽  
...  
Keyword(s):  
Doppler Ultrasound ◽  
Liver Tumors ◽  
Color Doppler ◽  
Color Doppler Ultrasound ◽  
Ultrasound Images

scholarly journals Efficacy Evaluation on the Color Doppler Ultrasound, Multislice Spiral CT Combined with Serum Markers in Diagnosis of Primary Hepatic Carcinoma

2021 ◽  
Author(s):  
Xiaolan Zhao ◽  
Yifang Xia ◽  
Chunjing Li ◽  
Dapeng Wang
Keyword(s):  
Doppler Ultrasound ◽  
High Speed ◽  
Color Doppler ◽  
Spiral Ct ◽  
Color Doppler Ultrasound ◽  
Alpha Fetoprotein ◽  
Control Group ◽  
Hepatic Carcinoma ◽  
Multislice Spiral Ct ◽  
Primary Hepatic Carcinoma

Background: The efficacy of color Doppler ultrasound, multislice spiral CT combined with serum alpha-fetoprotein (AFP) and alpha-fetoprotein heterogeneity (AFP-L3) in the diagnosis of primary hepatic carcinoma was evaluated. Methods: Seventy-nine patients with primary hepatic carcinoma (PHC group) and 50 patients with benign liver lesions (benign control group) admitted in Yantaishan Hospital (Yantai, China) from January 2016 to December 2018 were selected. The liver was scanned by color Doppler ultrasound and multiple multislice spiral CT. The serum AFP and AFP-L3 levels were detected by electrochemiluminescence. The value of color Doppler ultrasound, multislice spiral CT combined with serum AFP and AFP-L3 in diagnosis of primary liver cancer was retrospectively analyzed. Results: The color Doppler flow imaging (CDFI) showed a high-speed and high-resistance spectrum. The serum AFP and AFP-L3 levels of patients with primary hepatic carcinoma were significantly higher than those of the benign control group were (U=138.000 and 155.500, P=0.000 and 0.000), P<0.01. The sensitivity, accuracy and negative predictive value of color Doppler ultrasound, multislice spiral CT combined with serum AFP and AFP-L3 examinations for diagnosis of primary hepatic carcinoma were 96.20, 90.70 and 93.18%, which was significantly improved compared with each single examination (X2=27.888, 17.511 and 16.202, P=0.000, 0.002 and 0.003), P<0.01. Conclusion: Color Doppler ultrasound, multislice spiral CT combined with AFP and AFP-L3 examination could significantly improve the diagnosis efficiency of primary hepatic carcinoma, which was beneficial to early clinical diagnosis and early treatment.

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