Identificador persistente para citar o vincular este elemento:
https://accedacris.ulpgc.es/jspui/handle/10553/162482
| Título: | HyCervix: In Vivo Hyperspectral Cervix Dataset for Non-Invasive Detection of Precancerous and Cancerous Lesions | Autores/as: | Vega, Carlos Medina Ramos, Norberto Fidel León Martín, Sonia Raquel Fabelo Gómez, Himar Antonio Martín Martínez, Alicia Marrero Callicó, Gustavo Iván |
Clasificación UNESCO: | 32 Ciencias médicas 3314 Tecnología médica 320713 Oncología |
Palabras clave: | Trends Hyperspectral Imaging Colposcopy Cervical Cancer Clinical Data |
Fecha de publicación: | 2026 | Publicación seriada: | Data | Resumen: | Hyperspectral (HS) imaging has emerged as a promising tool for improving the non-invasive detection of different diseases, offering spatial and spectral information in a single imaging modality. In this work, we present a dataset of HS images of the in vivo human cervix, including different precancerous and cancerous lesions. The dataset comprises 77 HS images acquired from 77 patients during routine colposcopic examination. All images were captured using a clinical colposcope equipped with an HS camera, covering the spectral range from 470 to 900 nm. Each HS image is accompanied by detailed pixel-level annotations for different clinically relevant tissue classes: ectocervix, endocervix, cervical intraepithelial neoplasia lesions, and invasive carcinoma. These labels were established through expert colposcopic assessment and confirmed by cytology or biopsy. The dataset contains clinical data from these patients, including demographic information, colposcopy and biopsy findings, and clinical diagnoses. | URI: | https://accedacris.ulpgc.es/jspui/handle/10553/162482 | ISSN: | 2306-5729 | DOI: | 10.3390/data11030062 | Fuente: | Data [eISSN 2306-5729], v. 11 (3), (Marzo 2026) |
| Colección: | Artículos |
Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.