ArticleScientific reports2025
Feasibility study of hyperspectral colposcopy as a novel tool for detecting precancerous cervical lesions.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- In-vivo detection of cervical cancer lesions using hyperspectral colposcopy.Scientific reports · 2026Article
- From Image-Guided Surgery to Computer-Assisted Real-Time Diagnosis with Hyperspectral and Multispectral Imaging: A Systematic Review in Gynecologic Oncology.Diagnostics (Basel, Switzerland) · 2026Review
- Design and Characterization of a Hyperspectral Colposcope Based on Dual-LCTF VNIR Narrow-Band Illumination.Sensors (Basel, Switzerland) · 2026Article
- Development and clinical validation of a clinically translatable non-chip-on-tip transvaginal imaging system (GynoSight v2.0) for early detection of premalignant cervical lesions.Journal of biomedical optics · 2025Article
- Assessment of the Real-Time Photoelectric Detection Device (TruScreen) in Screening for Cervical Precancerous Lesions in Middle-Aged Women: An Observational Study.Risk management and healthcare policy · 2025Article
- Detection of Cervical Intraepithelial Neoplasia Using Hyperspectral Tissue Signatures.IEEE journal of translational engineering in health and medicine · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Cervical cancer remains a major global health concern, with a specially alarming incidence in younger women. Traditional detection techniques such as the Pap smear and colposcopy often lack sensitivity and specificity and are highly dependent on the experience of the gynaecologist. In response, this study proposes the use of Hyperspectral Imaging, a pioneering technology that combines traditional imaging with spectroscopy to provide detailed spatial and spectral information. Over a period of six-months, our custom-designed hyperspectral colposcope was used on 62 patients. The gathered data underwent a specialized preprocessing workflow using a PCA-based strategy for unsupervised segmentation of the cervical region. This process extracted spectral signatures from various tissue types, and our subsequent statistical analysis highlighted its ability to detect differences and alterations in the cervical tissue. This offers a promising avenue for improving the precision of cervical lesion diagnosis.
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Registered trials
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