eISSN: 1897-4309
ISSN: 1428-2526
Contemporary Oncology/Współczesna Onkologia
Current issue Archive Manuscripts accepted About the journal Supplements Addendum Special Issues Editorial board Abstracting and indexing Subscription Contact Instructions for authors Ethical standards and procedures
SCImago Journal & Country Rank
3/2019
vol. 23
 
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abstract:
Original paper

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

Łukasz Lasyk
,
Jakub Barbasz
,
Paweł Żuk
,
Artur Prusaczyk
,
Tomasz Włodarczyk
,
Ewa Prokurat
,
Wojciech Olszewski
,
Mariusz Bidziński
,
Piotr Baszuk
,
Jacek Gronwald

Contemp Oncol (Pozn) 2019; 23 (3): 174-177
Online publish date: 2019/10/31
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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.
keywords:

cervical cancer, cytology, automatic evaluation

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