scholarly journals Application Advances of Contrast-enhanced Ultrasound in Clinical Diagnosis and Treatment

2021 ◽  
Vol 9 (2) ◽  
pp. 98
Author(s):  
Zhou Xiaoyu ◽  
Peng Changfu
Keyword(s):  
Clinical Diagnosis ◽  
Diagnosis And Treatment ◽  
Contrast Enhanced Ultrasound ◽  
Contrast Enhanced

The Contrast-Enhanced Ultrasound Information Technology in the Treatment of Liver Tumors

2020 ◽  
Vol 10 (9) ◽  
pp. 2168-2174
Author(s):  
Xueping Yang ◽  
Xuemei Wang ◽  
Yao Zhang
Keyword(s):  
Experimental Data ◽  
Diagnostic Accuracy ◽  
Sparse Representation ◽  
Clinical Diagnosis ◽  
Liver Tumors ◽  
Data Sets ◽  
Contrast Enhanced Ultrasound ◽  
Accuracy Rate ◽  
Contrast Enhanced ◽  
Sparse Classification

Objective: To study the automatic diagnosis method of liver tumors in the contrast-enhanced ultrasound environment, assist doctors in the clinical diagnosis of liver tumors intuitively, conveniently, and accurately, thereby improve the cure rate of liver tumors. Methods: First, six sets of experimental data were constructed. The automatic diagnosis experiment of liver tumors through contrast-enhanced ultrasound was performed by the combination of sparse representation-based support vector machine (SVM) and principal component analysis (PCA)-based SVM, as well as the sparse representation classification method. The effect of classification decision principles on experiments was further studied. Results: The SVM method had an average effect on diagnostic accuracy. The average diagnostic accuracy of the six different experimental data sets was 76%, and the average diagnosis time was 300 s. The feature extraction method based on the combination of sparse representation and PCA was applied to the SVM method to achieve an optimal diagnosis. The average diagnosis accuracy rate could reach 87%, and the average time was more than 1,000 s. Using the sparse classification representation method, the diagnostic accuracy rate for the six experimental data sets constructed was above 93%, with a maximum of 99%, and the average time was 210 s. The sparse classification representation using the principle of minimum reconstruction error classification decision had an average diagnostic accuracy rate of 99% and an average time of 128 s. Conclusion: The sparse classification representation for the clinical diagnosis of liver tumors by contrast-enhanced ultrasound had high accuracy and consumed less time. Therefore, the constructed method was valuable.

Clinical diagnosis of veno-occlusive disease using contrast enhanced ultrasound

2018 ◽  
Vol 53 (10) ◽  
pp. 1369-1371 ◽  
Author(s):  
C. Trenker ◽  
K. Sohlbach ◽  
C. F. Dietrich ◽  
C. Görg
Keyword(s):  
Clinical Diagnosis ◽  
Occlusive Disease ◽  
Contrast Enhanced Ultrasound ◽  
Contrast Enhanced

scholarly journals Tumour targeted contrast enhanced ultrasound imaging dual-modal microbubbles for diagnosis and treatment of triple negative breast cancer

RSC Advances ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 5682-5691 ◽  
Author(s):  
Min Bai ◽  
Yang Dong ◽  
Hui Huang ◽  
Hao Fu ◽  
Yourong Duan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ultrasound Imaging ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Diagnosis And Treatment ◽  
Contrast Enhanced Ultrasound ◽  
Contrast Enhanced

Tumour targeted contrast-enhanced ultrasound imaging dual-modal microbubbles (PTX@RGD-MBs) combined with UTMD for diagnosing and treating triple negative breast cancer.

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