Cric searchable image database as a public platform for conventional pap smear cytology data
| العنوان: | Cric searchable image database as a public platform for conventional pap smear cytology data |
|---|---|
| المؤلفون: | Cláudia Martins Carneiro, Andrea Gomes Campos Bianchi, Mariana T. Rezende, Tales Mota Machado, Caio S. Costa, Daniela Ushizima, Paulo H. C. Oliveira, Raniere Silva, Fagner de O. Bernardo, Fátima N. S. de Medeiros, Alessandra Hermógenes Gomes Tobias |
| المصدر: | Scientific data, vol 8, iss 1 Scientific Data Scientific Data, Vol 8, Iss 1, Pp 1-8 (2021) |
| بيانات النشر: | eScholarship, University of California, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Statistics and Probability, Telemedicine, Computer science, Science, Uterine Cervical Neoplasms, Cervix Uteri, Library and Information Sciences, Cervical Cancer, Article, Education, Cancer screening, Machine Learning, Population screening, Databases, 03 medical and health sciences, 0302 clinical medicine, Clinical Research, Health care, medicine, Humans, Early Detection of Cancer, 030304 developmental biology, Cancer, Preventive medicine, Cervical cancer, High rate, 0303 health sciences, business.industry, Prevention, Health Services, medicine.disease, Data science, Automation, Computer Science Applications, Test (assessment), Identification (information), Networking and Information Technology R&D, Good Health and Well Being, Image database, Internet Use, 030220 oncology & carcinogenesis, Female, Statistics, Probability and Uncertainty, business, Biotechnology, Information Systems, Papanicolaou Test |
| الوصف: | Amidst the current health crisis and social distancing, telemedicine has become an important part of mainstream of healthcare, and building and deploying computational tools to support screening more efficiently is an increasing medical priority. The early identification of cervical cancer precursor lesions by Pap smear test can identify candidates for subsequent treatment. However, one of the main challenges is the accuracy of the conventional method, often subject to high rates of false negative. While machine learning has been highlighted to reduce the limitations of the test, the absence of high-quality curated datasets has prevented strategies development to improve cervical cancer screening. The Center for Recognition and Inspection of Cells (CRIC) platform enables the creation of CRIC Cervix collection, currently with 400 images (1,376 × 1,020 pixels) curated from conventional Pap smears, with manual classification of 11,534 cells. This collection has the potential to advance current efforts in training and testing machine learning algorithms for the automation of tasks as part of the cytopathological analysis in the routine work of laboratories. |
| وصف الملف: | application/pdf |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::412171072649ede8a4b98c0a9378f9db https://escholarship.org/uc/item/1717m4s3 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....412171072649ede8a4b98c0a9378f9db |
| قاعدة البيانات: | OpenAIRE |
| الوصف غير متاح. |