Laboratory Implementation and Efficacy Assessment of the ThinPrep Cervical Cancer Screening System

1998 ◽  
Vol 42 (1) ◽  
pp. 209-213 ◽  
Author(s):  
David R. Bolick ◽  
Dennis J. Hellman
Keyword(s):  
Cervical Cancer ◽  
Cancer Screening ◽  
Cervical Cancer Screening ◽  
Screening System ◽  
Efficacy Assessment

scholarly journals Computer-Assisted Screening for Cervical Cancer Using Digital Image Processing of Pap Smear Images

2020 ◽  
Vol 10 (5) ◽  
pp. 1800 ◽  
Author(s):  
Kyi Pyar Win ◽  
Yuttana Kitjaidure ◽  
Kazuhiko Hamamoto ◽  
Thet Myo Aung
Keyword(s):  
Image Processing ◽  
Cervical Cancer ◽  
Cancer Screening ◽  
Cervical Cancer Screening ◽  
Digital Image Processing ◽  
Digital Image ◽  
Pap Smear ◽  
Support Vector ◽  
Computer Assisted ◽  
Screening System

Cervical cancer can be prevented by having regular screenings to find any precancers and treat them. The Pap test looks for any abnormal or precancerous changes in the cells on the cervix. However, the manual screening of Pap smear in the microscope is subjective with poorly reproducible criteria. Therefore, the aim of this study was to develop a computer-assisted screening system for cervical cancer using digital image processing of Pap smear images. The analysis of Pap smear image is important in the cervical cancer screening system. There were four basic steps in our cervical cancer screening system. In cell segmentation, nuclei were detected using a shape-based iterative method, and the overlapping cytoplasm was separated using a marker-control watershed approach. In the features extraction step, three important features were extracted from the regions of segmented nuclei and cytoplasm. RF (random forest) algorithm was used as a feature selection method. In the classification stage, bagging ensemble classifier, which combined the results of five classifiers—LD (linear discriminant), SVM (support vector machine), KNN (k-nearest neighbor), boosted trees, and bagged trees—was applied. SIPaKMeD and Herlev datasets were used to prove the effectiveness of our proposed system. According to the experimental results, 98.27% accuracy in two-class classification and 94.09% accuracy in five-class classification was achieved using the SIPaKMeD dataset. When the results were compared with five classifiers, our proposed method was significantly better in two-class and five-class problems.

What Has Changed Since the Introduction of Human Papillomavirus Testing with the Cytology-Based Cervical Cancer Screening System in Japan A Social Experiment

2019 ◽  
Vol 63 (5) ◽  
pp. 385-390 ◽  
Author(s):  
Mariko Hashiguchi ◽  
Yoshifumi Nakao ◽  
Atsuko Honda ◽  
Atsushi Kawaguchi ◽  
Katsuyuki Hanashima ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Human Papillomavirus ◽  
Cancer Screening ◽  
Cervical Cancer Screening ◽  
City Government ◽  
Hpv Testing ◽  
Screening System ◽  
Social Experiment ◽  
Screening Programs ◽  
Incidence And Mortality

Background: Uterine cervical cancer is the fourth most common female cancer in the world. In Japan, we have an apparently low rate of joining cervical cancer screening programs compared with Western countries. Furthermore, the incidence and mortality rate of cervical cancer among the younger generation has been increasing. Object: The aim of this study was to assess the effectiveness of cervical cancer screening with human papillomavirus (HPV) testing and cytology in Japan. Methods: Collaborating with Saga City government, we initiated a cervical cancer screening system consisting of HPV testing and baseline cervical cytology from April 2011 as a social experiment. A total of 17,284 participants have been screened with this new combination system. Results: After HPV testing with cytology-based cervical cancer screening, the number of screenings done in women aged under 40 years has significantly increased. In addition, the number of women diagnosed with cervical intraepithelial neoplasia grade 3 has increased (25 of 14,025 vs. 146 of 23,049 under 50 years: p < 0.001). Conclusion: These data suggested that the introduction of HPV testing with cytology-based cervical cancer screening as an adjunct to conventional cytology resulted in better efficiency and more accurate screening among the Japanese population.

CytoBrain: Cervical Cancer Screening System Based on Deep Learning Technology

2021 ◽  
Vol 36 (2) ◽  
pp. 347-360
Author(s):  
Hua Chen ◽  
Juan Liu ◽  
Qing-Man Wen ◽  
Zhi-Qun Zuo ◽  
Jia-Sheng Liu ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Deep Learning ◽  
Cancer Screening ◽  
Cervical Cancer Screening ◽  
Learning Technology ◽  
Screening System

A Cervical Cancer Screening System and the Clinical Application

2016 ◽  
Author(s):  
Hao Ding ◽  
Mengyu Jia ◽  
Weiya Wang ◽  
Lihong Yang ◽  
Pengpeng Qu ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Cancer Screening ◽  
Cervical Cancer Screening ◽  
Clinical Application ◽  
Screening System

A Cervical Cancer Screening System Based on An Opto-electrical Joint Measurement

2015 ◽  
Vol 44 (4) ◽  
pp. 417001
Author(s):  
赵会娟 ZHAO Hui-juan ◽  
贾梦宇 JIA Meng-yu ◽  
王微雅 WANG Wei-ya ◽  
曲芃芃 QU Peng-peng ◽  
杨丽红 YANG Li-hong ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Cancer Screening ◽  
Cervical Cancer Screening ◽  
Screening System ◽  
Joint Measurement
Sign in / Sign up

Export Citation Format

Share Document