Szczegóły publikacji
Opis bibliograficzny
CompLung: comprehensive computer-aided diagnosis of lung cancer / Adam Pardyl, Dawid Rymarczyk, Joanna JAWOREK-KORJAKOWSKA, Dariusz KUCHARSKI, Andrzej BRODZICKI, Julia LASEK, Zofia SCHNEIDER, Iwona Kucybała, Andrzej Urbanik, Rafał Obuchowicz, Zbisław TABOR, Bartosz Zieliński // W: ECAI 2023 : 26th European Conference on Artificial Intelligence : including 12th conference on Prestigious Applications of Intelligent Systems (PAIS 2023) : September 30 - October 4, 2023, Kraków, Poland : proceedings / ed. by Kobi Gal, [et al.] ; European Association for Artificial Intelligence (EurAI), Polish Artificial Intelligence Society (PSSI). — Amsterdam : IOS Press BV, cop. 2023. — (Frontiers in Artificial Intelligence and Applications ; ISSN 0922-6389 ; vol. 372). — ISBN: 978-1-64368-436-9; e-ISBN: 978-1-64368-437-6. — S. 1835-1842. — Bibliogr. s. 1841-1842, Abstr. — Dod. abstrakt dostępny w: https://ecai2023.eu/acceptedpapers [2023-11-06]
Autorzy (12)
- Pardyl Adam
- Rymarczyk Dawid
- AGHJaworek-Korjakowska Joanna
- AGHKucharski Dariusz
- AGHBrodzicki Andrzej
- AGHLasek Julia
- AGHSchneider Zofia
- Kucybała Iwona
- Urbanik Andrzej
- Obuchowicz Rafał
- AGHTabor Zbisław
- Zieliński Bartosz
Dane bibliometryczne
| ID BaDAP | 149123 |
|---|---|
| Data dodania do BaDAP | 2023-11-06 |
| Tekst źródłowy | URL |
| DOI | 10.3233/FAIA230471 |
| Rok publikacji | 2023 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Creative Commons | |
| Wydawca | IOS Press |
| Konferencja | European Conference on Artificial Intelligence 2023 |
| Czasopismo/seria | Frontiers in Artificial Intelligence and Applications |
Abstract
Lung cancer is a leading cause of cancer-related deaths, and early diagnosis is crucial for its effective treatment. That is why computer-aided tools have been developed to support particular steps of CT scan analysis, including lung segmentation, suspicious region detection, and patient-level diagnosis. However, none of the previous approaches addressed this process comprehensively. To fill this gap, we introduce CompLung, a comprehensive tool for lung cancer diagnosis that performs all of the above-listed steps in an end-to-end manner. We have trained the CompLung architecture using the publicly available LIDC-IDRI dataset extended with lung segmentation masks obtained from our internal radiologists, which we make publicly available to boost the research on this emerging topic. Finally, we conduct extensive experiments and demonstrate the superior performance and interpretability of CompLung compared to existing methods for lung cancer diagnosis.
