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

Author:

Bian Peng1ORCID,Zhang Xiyu1ORCID,Liu Ruihong1ORCID,Li Huijie1ORCID,Zhang Qingqing1ORCID,Dai Baoling2ORCID

Affiliation:

1. Department of Statistics and Medical Record Management, Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China

2. Medical Office, Liaocheng Hospital of Traditional Chinese Medicine of Shandong Province, Liaocheng 252000, Shandong, China

Abstract

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.

Funder

National Key Research and Development Plan of China

Publisher

Hindawi Limited

Subject

Health Informatics,Biomedical Engineering,Surgery,Biotechnology

Reference21 articles.

1. Chronic Heart Failure

2. Chronic heart failure in the elderly: still a current medical problem;A. Skrzypek;Folia Medica Cracoviensia,2018

3. New insights into the pathogenesis and treatment of sarcopenia in chronic heart failure

4. Sarcopenia

5. Sarcopenia: revised European consensus on definition and diagnosis

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