Cervical nuclei segmentation through synergic conditional generative adversarial network in cervical smear images.

Cervical cancer is the second most common cancer among Indian women. Prevention and early detection can help reduce the incidence of cervical cancer. Taking care of health needs of the people and preventing diseases is a major concern for health, professionals. Planned teaching programme is one of the most effective teaching strategies, which can be used for improving the knowledge of people. Aim: The aim of this study was to find out the effectiveness of a planned teaching programme in improving the knowledge of women in prevention and early detection of cervical cancer. Material and Methods: Pre experimental design was used to assess the Effectiveness of Planned Teaching Programme (PTP) on knowledge regarding early detection and prevention of cervical cancer. Purposive sampling techniques were used to select 60 women in selected village in Gurugram. Informed written consent was taken from selected women. A structured questionnaire was administered to assess the knowledge on early detection and prevention of cervical cancer. The collected data was analyzed by using descriptive statistics and inferential statistics. Frequency and percentage distribution was used for demographic variables and assessing the knowledge on early detection and prevention of cervical cancer. Chi- square test was used to find out association between knowledge on early detection and prevention of cervical cancer among women and selected demographic variables. Result: The finding of the study revealed that pre test knowledge 35% had poor, 60% had average,5% had good knowledge regarding early detection and prevention of cervical cancer. Post test knowledge 0% had poor, 25% had average, 75% had good knowledge regarding early detection and prevention of cervical cancer. Knowledge was significantly associated with religion0.02 at significance of p<0.05 level. No association was found between knowledge and other demographic variables like age, education, occupation, marital status, number of children, health information. Conclusion: Planned teaching programme will be effective in improving knowledge regarding early detection and prevention of cervical cancer among women in selected villages in Gurugram.

Cervical cancer is a scary disease for women all over the world. This disease can actually be prevented and identified early. Pap smear is one of the tools of early detection to determine the presence of symptoms of cervical cancer. If women’s knowledge is good about pap smear’s early detection of cervical cancer, it can prevent the disease. The objective of this study was to know the effect of health education in women about pap smear which aids in early detection and prevention of cervical cancer. This was a quasi-experimental one group pretest, conducted without a control group at Murni Teguh Memorial Hospital (MTMH), Medan, North Sumatra from June to July 2018. There were 36 samples selected using purposive sampling. Wilcoxon signed-rank test was used for data analysis. The results of this study showed that there was a difference in the mean value of women's knowledge levels (p = 0. 000) before and after the intervention. The conclusion of this study was that there was a significant effect of health education in terms of an increase in the level of women's knowledge about pap smear’s early detection and prevention of cervical cancer. It is expected that health education about pap smear’s early detection and prevention of cervical cancer will prove to be very important in the future.

In this paper, we propose a framework for detection and classification of cervical cancer from pap smear images. Early detection and accurate diagnosis of cervical cancer can reduce the death rate of cervical cancer patients. Pap smear or pap test is the most popular technique for early detection of cervical cancer. However, the manual analysis is labor intensive and time consuming process which relies on expert cytologist. Hence, it is needed to develop a computer aided diagnosis system to make the pap smear test more accurate and reliable. The objective of this paper is to present an innovative idea of applying random forest algorithm (RF) as a feature selection method using proposed bagging ensemble classifier for improving the predictive performance. The four basic steps of cervical cancer detection and classification system, image enhancement, segmentation, feature extraction and classification were used. K-means clustering combining with morphology operations obtained good segmentation for cell nuclei and cytoplasm. The most important features, shape, color and texture of nuclei and cytoplasm were applied to detect cervical cancer. To improve the accuracy of prediction results, random forest (RF) algorithm was used as a feature selection method. In classification stage, bagging ensemble classifier was applied which aggregated the results of five classifiers, linear discriminant (LD), support vector machine (SVM), weighted k-nearest neighbor (KNN), boosted trees and bagged trees. Herlev data set was used to prove the effectiveness of our proposed method. According to the experimental results, the high classification accuracy was achieved with top10 features using our proposed combined classifier. The accuracy was 97.83% in two class problem and 81.54% in seven class problem. When the results were compared with five classifiers, our proposed method was significantly better in two class and seven class problems.

Cervical cancer is one of the most common types of cancer in women worldwide. The main cause of cervical cancer is infection with oncogenic types of Human Papilloma Virus (HPV), especially types 16 and 18. Early detection through methods such as Pap smear, IVA (Visual Inspection with Acetic Acid), and HPV DNA testing is very important to identify precancerous lesions before they develop into invasive cancer. Public education about cervical cancer prevention, including HPV vaccination, routine screening, and a healthy lifestyle, is a strategic step to reduce the incidence and mortality due to this disease. This community service program aims to increase public awareness of the importance of early detection and prevention of cervical cancer through a structured educational approach. Thus, it is hoped that a community can be created that is more aware of reproductive health and is able to take preventive measures against cervical cancer. Objective: to increase public understanding and knowledge about early detection of cervical cancer and its prevention. Method: Community service is carried out by providing education to the public about early detection of cervical cancer and its prevention. Results: The activity was carried out on Sunday, February 23, 2025, at PKM Chiba, Japan. Twenty-nine people attended community service activities. Educational activities were carried out from preparation to evaluation. The materials provided included early detection and prevention of cervical cancer. Conclusion: Community service activities went smoothly. This educational activity is expected to be recommended and continued by other health workers so that it can increase mothers' confidence in early detection and prevention of cervical cancer.

Cervical cancer, the fourth most common malignancy in women worldwide, continues to pose a significant threat to global health. Manual examination of the Pap smear image is time-consuming, labor-intensive, and prone to human error due to the large number of slides and subjective judgment. This study proposes a novel SegNet-based spatial pyramid pooling (SPP-SegNet) deep learning model for segmentation and a Squeeze-and-Excitation-based (SE-DenseNet201) model for classification, aimed at improving the accuracy of cervical cancer detection. The model incorporates the SPP bottleneck and atrous convolution in the SegNet framework, allowing for the extraction of multiscale spatial features and improving segmentation performance. The segmentation output is used as input for the classification task. The proposed method is evaluated on the Pomeranian and SIPaKMeD datasets. Segmentation results show that SPP-SegNet achieves 98.53% accuracy on the Pomeranian data set, exceeding standard SegNet, 97.86%. It also achieves 94.15% accuracy on the SIPaKMeD dataset, outperforming the standard SegNet, which is 90.95%. For classification, SE-DenseNet201 achieves 93% and 99% accuracy for the Pomeranian and SIPaKMeD binary classification, respectively, using the bounding box input. These results show that SPP-SegNet and SE-DenseNet201 can potentially automate cervical cell segmentation and classification, facilitating the early detection and diagnosis of cervical cancer.

Introduction: Cervical cancer is the second most common cancer among Indian women. Prevention and early detection can help reduce the incidence of cervical cancer. Taking care of health needs of the people and preventing diseases is a major concern for health, professionals. Planned teaching programme is one of the most effective teaching strategies, which can be used for improving the knowledge of people.Aim: The aim of this study was to find out the effectiveness of a planned teaching programme in improving the knowledge of women in prevention and early detection of cervical cancer.Material and Method: Pre experimental design was used to assess the Effectiveness of Planned Teaching Programme (PTP) on knowledge regarding early detection and prevention of cervical cancer. Purposive sampling techniques were used to select 60 women in selected village in Gurugram. Informed written consent was taken from selected women. A structured questionnaire was administered to assess the knowledge on early detection and prevention of cervical cancer. The collected data was analyzed by using descriptive statistics and inferential statistics. Frequency and percentage distribution was used for demographic variables and assessing the knowledge on early detection and prevention of cervical cancer. Chi-square test was used to find out association between knowledge on early detection and prevention of cervical cancer among women and selected demographic variables.Result: The finding of the study revealed that pre test knowledge 35% had poor, 60% had average,5% had good knowledge regarding early detection and prevention of cervical cancer. Post test knowledge 0% had poor, 25% had average, 75% had good knowledge regarding early detection and prevention of cervical cancer. Knowledge was significantly associated with religion 0.02 at significance of p<0.05 level. No association was found between knowledge and other demographic variables like age, education, occupation, marital status, number of children, health information.Conclusion: Planned teaching programme will be effective in improving knowledge regarding early detection and prevention of cervical cancer among women in selected villages in Gurugram.

Objective. Conduct a comprehensive assessment of the indicators of screening programs for early detection of breast and cervical cancer in the Gomel region.Materials and methods. A total of 7,611 first-time detected cases of breast cancer and 1,370 cases of cervical cancer in the Gomel region were analyzed for the period 2012-2022 (according to Belarusian Cancer Registry). The results of examination of 105130 participants of the screening program for early detection of breast cancer and 70258 participants of the screening program for early detection of cervical cancer were analyzed.Results. During the period 2017-2022, due to screening, 12% of cases of breast cancer were detected from the total number of newly diagnosed malignant breast pathologies. From 2018 to 2022, the proportion of newly detected cases of cervical cancer within the screening program increased from 0.83% to 2.61%, which indicates that the introduction of the screening program contributes to an increase in the detection of precancerous conditions of the cervix.Conclusions. The screening program for breast cancer and cervical cancer has shown its effectiveness in detecting new cases of malignant neoplasms of these localizations. An important result of the screening conducted in the Gomel region is the fact that the observed trend towards a decrease in the detection of breast cancer and cervical cancer in the early stages does not give any cause for optimism, as this is evidence of a deterioration in the structure of the detected pathology.

The present study was conducted to assess the awareness and practice regarding early detection and prevention of breast and cervical cancers among women of kudumbashree units. A quantitative approach and non experimental descriptive design was used for the study. The study was theoretically supported by Nola J Pender's revised health promotion model. A total of 504 women of kudumbashree units were selected using multistage sampling technique. The data was collected using socio personal data sheet, structured questionnaire to measure the awareness and a rating scale to rate the practice regarding early detection and prevention of breast and cervical cancers, all developed by the researcher. The data was analysed using descriptive and inferential statistics. The findings of the study revealed that 81.9% of women of kudumbashree units had average awareness and 59.5% of women of kudumbashree units had good practice. There was no significant correlation between awareness and practice among women of kudumbashree units regarding early detection and prevention of breast and cervical cancers. The selected variables namely education of women of kudumbashree units, occupation of women of kudumbashree units and previous exposure to information regarding breast or cervical cancers had association with awareness regarding early detection and prevention of breast and cervical cancers. Also, there is no association between practice regarding early detection and prevention of breast and cervical cancers and any of the selected variables. An information booklet was prepared on early detection and prevention of breast and cervical cancers and distributed to all study participants.

HIGHLIGHTS 1. Visual Inspection with Acetic Acid (VIA) method is used in midwifery for early detection of cervical cancer.2. Service period, knowledge, and attitudes are factors that affect a midwife's performance in using VIA method for cervical cancer detection. ABSTRACT Objective: This study examined the association between service period, knowledge, and attitudes toward the performance of midwives in the early detection of cervical cancer using the Visual Inspection with Acetic Acid (VIA) method in Banjarmasin, Indonesia. Materials and Methods: This is a cross-sectional study done in 26 Public Health Centers in Banjarmasin, Indonesia, from March to November 2020 involving 172 respondents. Samples were purposively selected using a non-probability sampling technique. Data collection instruments were questionnaire and Health Service reports. Data analysis was done computerized. Results: Out of 172 respondents, 67.4% of which had &gt; 10 years of service period, 67.4% had inadequate knowledge and 86% showed a positive attitude about early detection of cervical cancer using the IVA method, and 79.9% had poor performance in conducting early detection of cervical cancer using the IVA method. Results of Chi-square test showed the associations between the service period (p = 0.005), knowledge (p = 0.0001), and attitude (p = 0.005) with the performance of midwives in early detection of cervical cancer using the VIA method. Conclusion: Service period, knowledge, and attitudes were associated with the performance of midwives in the early detection of cervical cancer using the VIA method in Banjarmasin, Indonesia. Professional training programs should be taken into consideration in improving the performance of midwives in cervical cancer detection.

Background: In 2013 the prevalence of cervical cancer in West Sumatra was 0.9 per 1000 population. This data exceeds the Indonesian prevalence of 0.8 per 1000 population. Lack of public knowledge regarding early detection of cervical cancer is the cause of the high prevalence of cervical cancer. This study aims to determine the factors associated with the participation of women of childbearing age in the early detection of VIA method cervical cancer in Padang City Health Center in 2018.Method: This study was a cross sectional design, conducted from February to October 2018. The population was women who visited the Alai Health Center and Pegambiran Health Center with a total sample were 110 respondents. The sampling method uses consecutive sampling method. Data collection by interview using a questionnaire. Data were analyzed by Chi-square statistical test and logistic regression with 95% confidence degree.Result: The results showed that 60% of respondents had never done the early detection of VIA cervical cancer method. Statistical test results show there was a significant relationship between the level of knowledge (p = 0,000), attitude (p = 0,041), access to information (p = 0,000) and husband's support (p = 0,000) with the early detection of VIA cervical cancer method. The results of multivariate analysis showed that the most dominant variables affected the participation of women in early detection of cervical cancer, namely husband's support (p = 0,000) and POR = 46,693.

Background: Cervical cancer is an uncontrolled cell growth that occurs in the cervix caused by the Human Papilloma Virus (HPV) virus. Early detection programs for cervical cancer can be done in several ways, including Visual Inspection of Acetic Acid (IVA), pap smear, colposcopy, cervicography, and pap net. This method has been shown to reduce the incidence of invasive cervical cancer by the amount and mortality of cervical cancer. The purpose of this study was to determine the relationship between knowledge and attitudes towards Women of Childbearing Age (WCA) compliance in early detection of cervical cancer at the Ulak Karang Health Center in Padang City. Method: Cross Sectional. The population in this study was all WCA mothers (19-69 years old) in the working area of the Ulak Karang Health Center in Padang City as many as 2,916 people with a total sample of 97 people taken using quota sampling. This research was carried out in the working area of the Ulak Karang Health Center, Padang City in May-July 2023. The variables in this study are knowledge, attitudes and compliance with IVA examination. Data were analyzed univariately, bivariately (chi square) and multivariate. Results: There was a significant association between knowledge and WCA compliance in early detection of cervical cancer (p value 0.000). There was a significant relationship between attitude and WCA compliance in early detection of cervical cancer (p value 0.000). The relationship between knowledge and attitudes towards adherence is that there is a significant relationship between knowledge and attitudes towards WCA adherence in early detection of cervical cancer (p value 0.000). Conclusion: There is a relationship of knowledge and attitudes towards WCA compliance in early detection of cervical cancer.

Cervical cancer is one of the fastest-growing cancers affecting women, leading to a significant number of deaths. However, early detection and timely treatment can greatly reduce the mortality rate and improve the chances of recovery. A widely used method for the diagnosis of cancer is the manual analysis of tissue biopsy specimens on slides. This manual process of specimen examination is time-consuming and error-prone, resulting in an increasing interest in digitizing histopathological workflows to refine and expedite analysis. This paper has compiled a comprehensive review of automated cervical nuclei segmentation approaches in histopathological images. We have examined both deep learning and traditional image segmentation methods, working mechanisms, and their variants, as well as the datasets used to evaluate these approaches. To find relevant studies, we searched on platforms such as IEEE Xplore, Google Scholar, ACM Digital Library, SpringerLink, and ScienceDirect using keywords such as cervical nuclei, nuclear, and nucleus, deep learning network (DNN), convolutional neural networks (CNNs), cervical cytology or histopathology, and traditional or classical image segmentation methods. We reviewed 78 research papers on both classical image segmentation and deep learning-based techniques specifically designed for nuclei segmentation in cervical histopathological images, published from 2010 until October 2024. We organized these studies into two main categories: Classical image segmentation methods and deep learning approaches, subdividing them into relevant subcategories and compiled a comparative analysis of their results, identified ongoing challenges in nuclei segmentation, and highlighted opportunities and future prospects for this task. We discussed recent studies on cervical nuclei segmentation using automated methods. The implementation of automated image segmentation methods and their various extensions has significantly improved the performance of automated diagnostic systems for cervical cancer.

Cervical cancer is the second largest cancer in Indonesia after breast cancer with an estimated number of new cases of 32,469 (17.2%). Meanwhile, the coverage of early detection of cervical cancer is still far below the target, namely 10.4%, which is ideally 80%. As many as 70% of cervical cancer cases are found to be in an advanced stage, thereby increasing mortality in women. This indicates that women still have low interest in early detection of cervical cancer, namely using the IVA (Visual Inspection with Acetic Acid) method. This literature review aims to determine the factors that influence the behavior of women of childbearing age (WUS) for early detection of cervical cancer through the IVA test. This literature review uses Literature reviews such as articles in research journal databases, searches are carried out via the internet in the form of reviewing articles via Google Scholar. From the initial search results using keywords, 240 articles were obtained and after carrying out the inclusion and exclusion criteria, 9 articles were obtained that were relevant to the publication period starting from 2018-2022. From some of the literature, it was found that the factors that influence WUS behavior for early detection of cervical cancer through the IVA test are influenced by knowledge, attitudes, husband/family support, access and sources of information, access to health services supported by cadres and health workers and culture of shame and fear. knowledge and attitudes of WUS, husband's support, support from health workers, and access to information sources. All factors have a very important role in influencing the behavior of WUS in carrying out VIA examinations. To motivate WUS to carry out IVA, health workers can increase health education regarding cervical cancer and early detection of cervical cancer to husbands and WUS with attractive media to attract the interest and participation of WUS to participate in VIA tests to reduce the morbidity and mortality rates for cervical cancer in Indonesia.

AI-based cervical lesion segmentation in colposcopy images has significant potential in improving screening efficiency and accuracy. However, most current cervical lesion segmentation algorithms are insufficient for rapid image segmentation in mass screening due to heavy parameters and complex framework. Therefore, a lightweight algorithm segmentation for cervical lesion real-time screening system is urgently needed. In this paper, a novel lightweight LSIL + region segmentation framework termed Light-MDDNet is proposed and deployed, which uses the encoder-decoder architecture. In encoder stage, the first layer of MobileNetV2 module outputs shallow features which tend to be lost during multi-layer feature extraction. We also utilize the Denseaspp module to extract deeper semantic information. In the decoder stage, a multi-scale feature fusion (MFF) module is used to fuse multi-scale features. Finally, the algorithm is deployed and tested on the JETSON ORIN NX edge device in cervical lesion segmentation screening system. The experiments on 971 LSIL + colposcopy images of lesions processed with acetic acid show that our proposed model outperforms some state-of-the-art segmentation networks, with a pixel mean pixel accuracy (MPA) of 94.96% and an average speed per image of 19.60ms. After deployment on the mobile terminal, the segmentation accuracy of the model almost unchanged and the interference speed reduces to 31.57ms per image. The Light-MDDNet network achieves the best balance of accuracy and speed in cervical lesion segmentation, showing great potential for the deployment in the mass screening of cervical lesion.

Low-and-middle income countries (LMICs) contribute approximately 70% of global cancer deaths, and the cancer incidence in these countries is rapidly increasing. Sub-Saharan African (SSA) countries, including South Africa (SA), bear some of the world’s highest cancer case fatality rates, largely attributed to late diagnosis. We explored contextual enablers and barriers for early detection of breast and cervical cancers according to facility managers and clinical staff at primary healthcare clinics in the Soweto neighbourhood of Johannesburg, South Africa. We conducted qualitative in-depth interviews (IDIs) between August and November 2021 amongst 13 healthcare provider nurses and doctors as well as 9 facility managers at eight public healthcare clinics in Johannesburg. IDIs were audio-recorded, transcribed verbatim, and entered into NVIVO for framework data analysis. Analysis was stratified by healthcare provider role and identified apriori around the themes of barriers and facilitators for early detection and management of breast and cervical cancers. Findings were conceptualised within the socioecological model and then explored within the capability, opportunity and motivation model of behaviour (COM-B) for pathways that potentially influence the low screening provision and uptake. The findings revealed provider perceptions of insufficient South African Department of Health (SA DOH) training support and staff rotations resulting in providers lacking knowledge and skills on cancer, screening policies and techniques. This coupled with provider perceptions of poor patient cancer and screening knowledge revealed low capacity for cancer screening. Providers also perceived opportunity for cancer screening to be undermined by the limited screening services mandated by the SA DOH, insufficient providers, inadequate facilities, supplies and barriers to accessing laboratory results. Providers perceived women to prefer to self-medicate and consult with traditional healers and access primary care for curative services only. These findings compound the low opportunity to provide and demand cancer screening services. And because the National SA Health Department is perceived by providers not to prioritize cancer nor involve primary care stakeholders in policy and performance indicator development, overworked, unwelcoming providers have little motivation to learn screening skills and provide screening services. Providers reported that patients preferred to go elsewhere and that women perceived cervical cancer screening as painful. These perceptions must be confirmed for veracity among policy and patient stakeholders. Nevertheless, cost-effective interventions can be implemented to address these perceived barriers including multistakeholder education, mobile and tent screening facilities and using existing community fieldworkers and NGO partners in providing screening services. Our results revealed provider perspectives of complex barriers to the early detection and management of breast and cervical cancers in primary health clinic settings in Greater Soweto. These barriers together appear potentially to produce compounding effects, and therefore there is a need to research the cumulative impact but also engage with stakeholder groups to verify findings and create awareness. Additionally, opportunities do exist to intervene across the cancer care continuum in South Africa to address these barriers by improving the quality and volume of provider cancer screening services, and in turn, increasing the community demand and uptake for these services.