ArticleProceedings of SPIE--the International Society for Optical Engineering2016
Superpixel-based spectral classification for the detection of head and neck cancer with hyperspectral imaging.
Article in Proceedings of SPIE--the International Society for Optical Engineering, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Medical hyperspectral imaging: an updated review of technology advancements and biomedical applications.Journal of biomedical optics · 2026Pooled it
- An Ensemble Learning Method for Detection of Head and Neck Squamous Cell Carcinoma Using Polarized Hyperspectral Microscopic Imaging.Proceedings of SPIE--the International Society for Optical Engineering · 2024Article
- Systematic meta-analysis of computer-aided detection to detect early esophageal cancer using hyperspectral imaging.Biomedical optics express · 2023Article
- Comparison of Whiskbroom and Pushbroom darkfield elastic light scattering spectroscopic imaging for head and neck cancer identification in a mouse model.Analytical and bioanalytical chemistry · 2021Article
- Automatic detection of head and neck squamous cell carcinoma on pathologic slides using polarized hyperspectral imaging and machine learning.Proceedings of SPIE--the International Society for Optical Engineering · 2021Article
- Surgical spectral imaging.Medical image analysis · 2020Review
- Article
- Development of a new polarized hyperspectral imaging microscope.Proceedings of SPIE--the International Society for Optical Engineering · 2020Article
- Adaptive deep learning for head and neck cancer detection using hyperspectral imaging.Visual computing for industry, biomedicine, and art · 2019Article
- Detection and delineation of squamous neoplasia with hyperspectral imaging in a mouse model of tongue carcinogenesis.Journal of biophotonics · 2018Article
- Deep Learning based Classification for Head and Neck Cancer Detection with Hyperspectral Imaging in an Animal Model.Proceedings of SPIE--the International Society for Optical Engineering · 2017Article
- Polarized hyperspectral microscopic imaging for collagen visualization on pathologic slides of head and neck squamous cell carcinoma.Proceedings of SPIE--the International Society for Optical EngineeringArticle
- Polarized Hyperspectral Microscopic Imaging for White Blood Cells on Wright-Stained Blood Smear Slides.Proceedings of SPIE--the International Society for Optical EngineeringArticle
- Polarized Hyperspectral Microscopic Imaging for Zebrafish.Proceedings of SPIE--the International Society for Optical EngineeringArticle
- Automatic detection of head and neck squamous cell carcinoma on pathologic slides using polarized hyperspectral imaging and deep learning.Proceedings of SPIE--the International Society for Optical EngineeringArticle
- Thyroid Carcinoma Detection on Whole Histologic Slides Using Hyperspectral Imaging and Deep Learning.Proceedings of SPIE--the International Society for Optical EngineeringArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications. HSI acquires two dimensional images at various wavelengths. The combination of both spectral and spatial information provides quantitative information for cancer detection and diagnosis. This paper proposes using superpixels, principal component analysis (PCA), and support vector machine (SVM) to distinguish regions of tumor from healthy tissue. The classification method uses 2 principal components decomposed from hyperspectral images and obtains an average sensitivity of 93% and an average specificity of 85% for 11 mice. The hyperspectral imaging technology and classification method can have various applications in cancer research and management.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.