dc.contributor.author | Myślicka, Maria | |
dc.contributor.author | Kawala-Sterniuk, Aleksandra | |
dc.contributor.author | Bryniarska, Anna | |
dc.contributor.author | Sudoł, Adam | |
dc.contributor.author | Podpora, Michał | |
dc.contributor.author | Gasz, Rafał | |
dc.contributor.author | Martinek, Radek | |
dc.contributor.author | Vilímková Kahánková, Radana | |
dc.contributor.author | Vilímek, Dominik | |
dc.contributor.author | Pelc, Mariusz | |
dc.contributor.author | Mikołajewski, Dariusz | |
dc.date.accessioned | 2024-10-31T16:33:44Z | |
dc.date.available | 2024-10-31T16:33:44Z | |
dc.date.issued | 2024 | |
dc.identifier.citation | Archives of Dermatological Research. 2024, vol. 316, issue 4, art. no. 99. | cs |
dc.identifier.issn | 0340-3696 | |
dc.identifier.issn | 1432-069X | |
dc.identifier.uri | http://hdl.handle.net/10084/155237 | |
dc.description.abstract | This paper presents the most current and innovative solutions applying modern digital image processing methods for the
purpose of skin cancer diagnostics. Skin cancer is one of the most common types of cancers. It is said that in the USA only,
one in five people will develop skin cancer and this trend is constantly increasing. Implementation of new, non-invasive
methods plays a crucial role in both identification and prevention of skin cancer occurrence. Early diagnosis and treatment
are needed in order to decrease the number of deaths due to this disease. This paper also contains some information regard
ing the most common skin cancer types, mortality and epidemiological data for Poland, Europe, Canada and the USA. It
also covers the most efficient and modern image recognition methods based on the artificial intelligence applied currently
for diagnostics purposes. In this work, both professional, sophisticated as well as inexpensive solutions were presented.
This paper is a review paper and covers the period of 2017 and 2022 when it comes to solutions and statistics. The authors
decided to focus on the latest data, mostly due to the rapid technology development and increased number of new methods,
which positively affects diagnosis and prognosis. | cs |
dc.language.iso | en | cs |
dc.publisher | Springer Nature | cs |
dc.relation.ispartofseries | Archives of Dermatological Research | cs |
dc.relation.uri | https://doi.org/10.1007/s00403-024-02828-1 | cs |
dc.rights | Copyright © 2024, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature | cs |
dc.subject | image processing | cs |
dc.subject | data analysis | cs |
dc.subject | skin cancer diagnostics | cs |
dc.subject | diomedical engineering | cs |
dc.title | Review of the application of the most current sophisticated image processing methods for the skin cancer diagnostics purposes | cs |
dc.type | article | cs |
dc.identifier.doi | 10.1007/s00403-024-02828-1 | |
dc.type.status | Peer-reviewed | cs |
dc.description.source | Web of Science | cs |
dc.description.volume | 316 | cs |
dc.description.issue | 4 | cs |
dc.description.firstpage | art. no. 99 | cs |
dc.identifier.wos | 001176065900002 | |