An evaluation of the construction of the device along with the software for digital archiving, sending the data, and supporting the diagnosis of cervical cancer.
automatic evaluation
cervical cancer
cytology
Journal
Contemporary oncology (Poznan, Poland)
ISSN: 1428-2526
Titre abrégé: Contemp Oncol (Pozn)
Pays: Poland
ID NLM: 101233223
Informations de publication
Date de publication:
2019
2019
Historique:
received:
17
05
2019
accepted:
30
05
2019
entrez:
5
12
2019
pubmed:
5
12
2019
medline:
5
12
2019
Statut:
ppublish
Résumé
Cervical cancer is still an important cause of mortality among women in a number of countries. There are effective methods of prevention and early diagnosis, but they require well-trained medical professionals including cytologists. Within this project, we built a prototype of a new device together with implemented software using U-NET and CNN architectures of neural networks (ANN), to convert the currently used optical microscopes into fully independent scanning and evaluating systems for cytological samples. To evaluate the specificity and sensitivity of the system, 2058 (2000 normal and 58 abnormal samples) consecutive liquid-based cytology (LBC) samples were analysed. The observed sensitivity and specificity to distinguish normal and abnormal samples was 100%. We observed slight incompatibility in the evaluation of the type of abnormality. The use of ANN is promising for increasing the effectiveness of cervical screening. The low cost of neural network usage further increases the potential areas of application of the presented method. Further refinement of neural networks on a larger sample size is required to evaluate the software.
Identifiants
pubmed: 31798334
doi: 10.5114/wo.2019.85617
pii: 85617
pmc: PMC6883966
doi:
Types de publication
Journal Article
Langues
eng
Pagination
174-177Informations de copyright
Copyright: © 2019 Termedia Sp. z o. o.
Déclaration de conflit d'intérêts
The authors declare no conflict of interest.
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