Efficacy, Feasibility and Acceptability of a Mediterranean Diet Intervention on Hormonal, Metabolic and Anthropometric Measures in Overweight and Obese Women with Polycystic Ovary Syndrome: Study Protocol

Scannell, Nicole; Moran, Lisa J.; Mantzioris, Evangeline; Cowan, Stephanie; Villani, Anthony

doi:10.3390/metabo12040311

Cited by 5 publications

(4 citation statements)

References 94 publications

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“…The concept of the Chan-Vese method is to segregate the pixels using the active contour model based on curved evolution and deformation to identify the boundary of the region of interest without determining the edge boundary [39]. This method is formulated by minimizing the energy function for a domain image, Ω, of an image I 0 (x,y) by adding some regularization term, which is the length of parameterized curve of the image, C, and/or area of the region inside C. The formulation is displayed in Equation ( 5): (5) where the fixed parameters are µ ≥ 0, ν ≥ 0 and λ 1 ,λ 2 > 0. The energy function c 1 , c 2 are the averages of the regions that approximate the image intensity inside and outside C expressed in the equation.…”

Section: The Chan-vese Methodsmentioning

confidence: 99%

“…This syndrome produces side effects related to women's overall health, such as abnormal hair growth, weight gain, irregular menstrual cycle, infertility and depression [2,3]. Almost 70% of women with PCOS suffer from infertility [4,5], and this condition is one of the common reasons for female infertility [6,7]. PCOS occurs in women during their reproductive years [8][9][10], between 18 and 45 years old.…”

Section: Introductionmentioning

confidence: 99%

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Performance Analysis of a Novel Hybrid Segmentation Method for Polycystic Ovarian Syndrome Monitoring

et al. 2023

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Experts have used ultrasound imaging to manually determine follicle count and perform measurements, especially in cases of polycystic ovary syndrome (PCOS). However, due to the laborious and error-prone process of manual diagnosis, researchers have explored and developed medical image processing techniques to help with diagnosing and monitoring PCOS. This study proposes a combination of Otsu’s thresholding with the Chan–Vese method to segment and identify follicles in the ovary with reference to ultrasound images marked by a medical practitioner. Otsu’s thresholding highlights the pixel intensities of the image and creates a binary mask for use with the Chan–Vese method to define the boundary of the follicles. The acquired results were compared between the classical Chan–Vese method and the proposed method. The performances of the methods were evaluated in terms of accuracy, Dice score, Jaccard index and sensitivity. In overall segmentation evaluation, the proposed method showed superior results compared to the classical Chan–Vese method. Among the calculated evaluation metrics, the sensitivity of the proposed method was superior, with an average of 0.74 ± 0.12. Meanwhile, the average sensitivity for the classical Chan–Vese method was 0.54 ± 0.14, which is 20.03% lower than the sensitivity of the proposed method. Moreover, the proposed method showed significantly improved Dice score (p = 0.011), Jaccard index (p = 0.008) and sensitivity (p = 0.0001). This study showed that the combination of Otsu’s thresholding and the Chan–Vese method enhanced the segmentation of ultrasound images.

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Section: The Chan-vese Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance Analysis of a Novel Hybrid Segmentation Method for Polycystic Ovarian Syndrome Monitoring

et al. 2023

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“…The diagnosis of PCOS is based on clinical presentation and laboratory tests, including hormonal assays and ultrasound imaging. Among these, ultrasound imaging is an essential tool for the diagnosis of PCOS, as it can detect the presence of cysts and other morphological changes in the ovaries.Conventional ultrasound imaging indiagnosingthe PCOS involves the use of static images, which are obtained by capturing a snapshot of the ovaries during a single examination [3][4][5]. However, PCOS is a dynamic disorder, and the presence and morphology of cysts can vary over time, depending on various factors such as hormonal fluctuations and treatment interventions.…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning based Improvised Follicle Polycystic Ovarian Detection Through Ultrasound Images Through IOT

Kachibhotla Srinivas

2023

IJRITCC

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Polycystic ovarian syndrome which is commonly called as PCOS is a endocrine malfunction affecting women of reproductive age. Its diagnosis involves in detection of multiple small follicles mainly in the ovaries through ultrasound imaging. However, manual detection is time-consuming, subjective, and prone to errors. Hence, this study proposes an improvised follicle PCOS detection method using machine learning(Random Forest and Logistic Regression) from a sequence of given ultrasound images. The proposed method involves pre-processing the ultrasound images through IoT, followed by segmenting and extracting follicle features. Subsequently, a machine learning model is trained to classify the extracted features as normal or PCOS cases. The proposed method's performance is evaluated on a dataset of 400 ultrasound images from 50 patients, including 25 PCOS cases and 25 healthy controls. The experimental results demonstrate that the proposed method achieves a high classification accuracy of 93.75% and an AUC of 0.96. In addition, the proposed methodology outperforms in comparison with the state-of-the-art PCOS detection methods in terms of accuracy, sensitivity, specificity, and AUC. The proposed method also provides a quantitative measure of the severity of PCOS based on the number and size of the follicles detected.

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“…For these reasons, to reduce the risk factors associated with NCDs, such as overweight and obesity, emphasis should be placed on the promotion of healthy diets, physical activity, smoking cessation, protection against alcohol consumption, as well as support for effective interventions aimed at changing environments so that the healthiest options are also the easiest [ 4 , 5 ]. In this contextual framework, the Mediterranean diet (MD) is presented as a healthy dietary model capable of guaranteeing adequate nutrient intake, preventing and reducing complications associated with NCDs, regulating body weight, and having a low environmental impact [ 6 , 7 , 8 , 9 ]. At present, numerous studies suggest that adherence to the Mediterranean Diet (AMD) plays an important role in the primary and secondary prevention of cardiovascular diseases (CVD), in addition to improving health in people with various pathologies [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Health Determinants Associated with the Mediterranean Diet: A Cross-Sectional Study

2022

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Introduction: The Mediterranean diet (MD) has been shown to be a good tool for the prevention of obesity and other chronic noncommunicable diseases (NCDs) and to have a low environmental impact. The aim of the present study was to evaluate the relationship between declared morbidity, lifestyles and other sociodemographic factors with high adherence to the MD (AMD) in an adult population in southeastern Spain. Material and Methods: We conducted a cross-sectional study of a sample (n = 2728) representative of a non-institutionalized population ≥16 years. The data corresponded to the 2010-11 Nutrition Survey of the Valencian Community. The AMD was assessed using the Mediterranean Diet Adherence Screener questionnaire. The association of variables and high AMD was assessed by univariate and multivariate logistic regression determining crude and adjusted odds ratios. Results: Multivariate analysis showed that age 45 years or older, living with a partner, eating between meals, and not smoking were associated with high AMD. The age groups 45–64 years and 65 years or older showed the strongest association with high AMD in both sexes. Conclusion: The investigation showed a generational loss of AMD. People older than 45 years and living in company are more likely to adhere to DM, the risk group being young people living alone and smokers.

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Efficacy, Feasibility and Acceptability of a Mediterranean Diet Intervention on Hormonal, Metabolic and Anthropometric Measures in Overweight and Obese Women with Polycystic Ovary Syndrome: Study Protocol

Cited by 5 publications

References 94 publications

Performance Analysis of a Novel Hybrid Segmentation Method for Polycystic Ovarian Syndrome Monitoring

Performance Analysis of a Novel Hybrid Segmentation Method for Polycystic Ovarian Syndrome Monitoring

A Machine Learning based Improvised Follicle Polycystic Ovarian Detection Through Ultrasound Images Through IOT

Health Determinants Associated with the Mediterranean Diet: A Cross-Sectional Study

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