HyCervix: In Vivo Hyperspectral Cervix Dataset for Non-Invasive Detection of Precancerous and Cancerous Lesions

Abstract

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. Dataset: The data presented in this study are openly available in Zenodo at https://doi.org/10.5281/zenodo.18208664. Dataset License: CC-BY