[S] Annotated Pap cell images and smear slices for cell classification

A tétel rövid nézete
dc.contributor.authorKupas, David
dc.contributor.authorHajdu, Andras
dc.contributor.authorKovacs, Ilona
dc.contributor.authorHargitai, Zoltan
dc.contributor.authorSzombathy, Zita
dc.contributor.authorHarangi, Balazs
dc.contributor.authorKupas Dávid (2024-) (xxx)
dc.contributor.authorHajdu András (1973-) (matematikus, informatikus)
dc.contributor.authorKovács Ilona (1965-) (patológus)
dc.contributor.authorHargitai Zoltán (2024-) (xxx)
dc.contributor.authorSzombathy Zita (2024-) (xxx)
dc.contributor.authorHarangi Balázs (1986-) (programtervező matematikus)
dc.contributor.submitterdepAdattudomány és Vizualizáció Tanszék -- 905
dc.contributor.submitterdepIK
dc.contributor.submitterdepDebreceni Egyetem
dc.contributor.submitterdepDebreceni Egyetem - Kenézy Kórház - Patológia Tanszék
dc.date.accessioned2024-07-24T07:49:08Z
dc.date.available2024-07-24T07:49:08Z
dc.date.oa2025-01-31
dc.date.updated2024-07-24T07:49:08Z
dc.description.abstractMachine learning-based systems have become instrumental in augmenting global efforts to combat cervical cancer. A burgeoning area of research focuses on leveraging artificial intelligence to enhance the cervical screening process, primarily through the exhaustive examination of Pap smears, traditionally reliant on the meticulous and labor-intensive analysis conducted by specialized experts. Despite the existence of some comprehensive and readily accessible datasets, the field is presently constrained by the limited volume of publicly available images and smears. As a remedy, our work unveils APACC (Annotated PAp cell images and smear slices for Cell Classification), a comprehensive dataset designed to bridge this gap. The APACC dataset features a remarkable array of images crucial for advancing research in this field. It comprises 103,675 annotated cell images, carefully extracted from 107 whole smears, which are further divided into 21,371 sub-regions for a more refined analysis. This dataset includes a vast number of cell images from conventional Pap smears and their specific locations on each smear, offering a valuable resource for in-depth investigation and study. © The Author(s) 2024.
dc.description.correctorLB
dc.identifier.citationScientific Data. -11 : 1 (2024), p. 1-8. -Sci Data. -2052-4463
dc.identifier.doi10.1038/s41597-024-03596-3
dc.identifier.issn2052-4463
dc.identifier.opachttps://ebib.lib.unideb.hu/ebib/CorvinaWeb?action=cclfind&resultview=long&ccltext=idno+BIBFORM122891
dc.identifier.urihttps://hdl.handle.net/2437/377016
dc.identifier.urlhttps://www.nature.com/articles/s41597-024-03596-3
dc.languageeng
dc.rights.accessopen access journal
dc.subject.otheridegen nyelvű folyóiratközlemény külföldi lapban
dc.subject.otherFemale
dc.subject.otherHumans
dc.subject.otherMachine Learning
dc.subject.otherPapanicolaou Test
dc.subject.otherUterine Cervical Neoplasms
dc.subject.otherVaginal Smears
dc.title[S] Annotated Pap cell images and smear slices for cell classification
Fájlok
Eredeti köteg (ORIGINAL bundle)
Megjelenítve 1 - 1 (Összesen 1)
Nincs kép
Név:
FILE_UP_0_s41597-024-03596-3.pdf
Méret:
1.58 MB
Formátum:
Adobe Portable Document Format
Leírás:
Kiadói változat
Letöltés
Gyűjtemények
Publikációs Adatbázis