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      Intelligent Noise Reduction Algorithm to Evaluate the Correlation between Human Fat Deposits and Uterine Fibroids under Ultrasound Imaging

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          Abstract

          This study aimed to realize the automatic diagnosis of fatty degeneration of uterine fibroids. In this study, the traditional nonlocal means (NLM) algorithm was improved by changing the Euclidean distance and introducing a cosine function and applied to the ultrasonic imaging intelligent diagnosis of patients with fatty degeneration of uterine fibroids. Then, the noise reduction effect of the improved NLM algorithm was evaluated based on several indicators, such as peak signal-to-noise ratio (PSNR), mean square error (MSE), contrast-to-noise ratio (CNR), figure of merit (FOM), and structural similarity (SSIM). The accuracy, sensitivity, specificity, and F1 score were adopted to evaluate the improved NLM algorithm for diagnosing fatty degeneration of uterine fibroids, and the Perona–Malik (PM) algorithm and NLM algorithm were used for comparative analysis. The results showed that after the ultrasound images of patients with uterine fibroids were denoised using the improved NLM algorithm, the PSNR, MSE, CNR, FOM, and SSIM were obviously better than the same indicators of the image processed with the PM algorithm and the NLM algorithm, and the differences were statistically significant ( P < 0.05). The diagnosis results of patients with fatty degeneration of uterine fibroids found that there was only one patient with missed diagnosis after the ultrasound image was processed with NLM algorithm, and there was no statistical difference between the improved NLM algorithm and the assisted diagnosis accuracy of the pathological examination results ( P > 0.05). The average noise reduction time of the PM algorithm, NLM algorithm, and the improved NLM algorithm was 16.38 ± 4.33 s, 18.01 ± 5.14 s, and 23.81 ± 4.62 s, respectively. The diagnosis rate before improvement was 75.0%, the diagnosis accuracy rate for PM was 79.69%, and that after improvement was 85.94%. In summary, the improved NLM algorithm showed a good noise reduction effect on ultrasound images of patients with uterine fibroids, could improve the diagnosis accuracy of fatty degeneration of uterine fibroids, and could assist clinicians in the ultrasound imaging diagnosis of patients with uterine fibroids.

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          Most cited references31

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          Extracellular matrix in uterine leiomyoma pathogenesis: a potential target for future therapeutics.

          Uterine leiomyoma (also known as fibroid or myoma) is the most common benign tumor of the uterus found in women of reproductive age. It is not usually fatal but can produce serious clinical symptoms, including excessive uterine bleeding, pelvic pain or pressure, infertility and pregnancy complications. Due to lack of effective medical treatments surgery has been a definitive choice for the management of this tumor.
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            Uterine leiomyosarcoma: Epidemiology, contemporary treatment strategies and the impact of uterine morcellation

            Leiomyosarcoma, a rare tumor subtype, accounts for 1% of all uterine malignancies, but contributes to a significant proportion of uterine cancer deaths. Surgery is considered the mainstay of treatment for all soft tissue sarcomas, including uterine variants. However, uterine leiomyosarcoma is challenging to diagnose preoperatively and can mimic the appearance of benign uterine leiomyomas. Recently, concerns have grown in this regard, as surgeons have utilized uterine morcellation and myomectomy procedures unknowingly in the setting of occult uterine sarcoma. Because of aggressive tumor biology and relative chemotherapy and radiotherapy resistance, efficacious therapies to achieve prolonged survival or cure in those with both early and advanced-stage uterine leiomyosarcoma have been elusive. The strongest determinant of survival remains stage at diagnosis, though prediction models may provide a more accurate prognosis. Given the aggressive nature of this sarcoma subtype, novel early detection strategies and targeted therapies are the focus of several recently published and ongoing studies. While gemcitabine/docetaxel and doxorubicin remain the most active regimens in the treatment of advanced or recurrent disease, currently available cytotoxic regimens remain inadequate, with 5-year disease-specific survival of <30%. Pazopanib, trabectedin and olaratumab, are FDA-approved, targeted therapies with activity in uterine and other leiomyosarcomas, while aromatase inhibitors and immunotherapies are under active investigation. This review provides a critical appraisal of the literature regarding the contemporary surgical and medical management of uterine leiomyosarcoma, the role of targeted therapies, and the implications of uterine morcellation on gynecologic surgical practice.
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              Noise and spatial resolution properties of a commercially available deep learning-based CT reconstruction algorithm.

              To characterize the noise and spatial resolution properties of a commercially available deep learning-based computed tomography (CT) reconstruction algorithm.
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                Author and article information

                Contributors
                Journal
                J Healthc Eng
                J Healthc Eng
                JHE
                Journal of Healthcare Engineering
                Hindawi
                2040-2295
                2040-2309
                2021
                30 November 2021
                : 2021
                : 5390219
                Affiliations
                1Department of Ultrasound, Affiliated Hospital of Zunyi Medical University, Zunyi 563000, Guizhou, China
                2Department of Ultrasound Medicine, Haikou Hospital of the Maternal and Child Health, Haikou 571100, Hainan, China
                Author notes

                Academic Editor: Chinmay Chakraborty

                Author information
                https://orcid.org/0000-0002-5803-0590
                https://orcid.org/0000-0002-7119-2607
                https://orcid.org/0000-0002-7899-4020
                https://orcid.org/0000-0002-0402-2683
                https://orcid.org/0000-0003-3730-8685
                https://orcid.org/0000-0002-2607-9576
                Article
                10.1155/2021/5390219
                8654549
                34900194
                1e9931c1-f598-45ec-8ab0-69c342ec9b07
                Copyright © 2021 Yan Luo et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 September 2021
                : 3 November 2021
                Funding
                Funded by: 2020 Hainan Health Industry Scientific Research Project
                Award ID: 20A200006
                Categories
                Research Article

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