ArticleJournal of biomedical optics2019
Optical biopsy of head and neck cancer using hyperspectral imaging and convolutional neural networks.
Article in Journal of biomedical optics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 2 of them syntheses that pooled it.
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Who cites it
40 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Medical hyperspectral imaging: an updated review of technology advancements and biomedical applications.Journal of biomedical optics · 2026Pooled it
- Hyperspectral imaging for tumor resection guidance in surgery: a systematic review of preclinical and clinical studies.Journal of biomedical optics · 2025Pooled it
- Toward real-time margin assessment in breast-conserving surgery with hyperspectral imaging.Scientific reports · 2025Article
- Systematic meta-analysis of computer-aided detection to detect early esophageal cancer using hyperspectral imaging.Biomedical optics express · 2023Article
- Effects of dimension reduction of hyperspectral images in skin gross pathology.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2023Article
- Signal to noise ratio quantifies the contribution of spectral channels to classification of human head and neck tissuesJournal of biomedical optics · 2023Article
- Deep Learning in Medical Hyperspectral Images: A Review.Sensors (Basel, Switzerland) · 2022Review
- Review
- Hyperspectral imaging for tumor segmentation on pigmented skin lesions.Journal of biomedical optics · 2022Article
- Comparison of preprocessing techniques to reduce nontissue-related variations in hyperspectral reflectance imaging.Journal of biomedical optics · 2022Article
- Label-free hyperspectral imaging and deep-learning prediction of retinal amyloid β-protein and phosphorylated tau.PNAS nexus · 2022Article
- Assessment of angle-dependent spectral distortion to develop accurate hyperspectral endoscopy.Scientific reports · 2022Article
- Programmable black phosphorus image sensor for broadband optoelectronic edge computing.Nature communications · 2022Article
- Hyperspectral Imaging for Tissue Classification after Advanced Stage Ovarian Cancer Surgery-A Pilot Study.Cancers · 2022Article
- Review on the Application of Hyperspectral Imaging Technology of the Exposed Cortex in Cerebral Surgery.Frontiers in bioengineering and biotechnology · 2022Review
- Real-time calibrating polarization-sensitive diffuse reflectance handheld probe characterizes clinically relevant anatomical locations of oral tissueBiomedical optics express · 2022Article
- Hyperspectral imaging and artificial intelligence to detect oral malignancy - part 1 - automated tissue classification of oral muscle, fat and mucosa using a light-weight 6-layer deep neural network.Head & face medicine · 2021Article
- Multiparametric Radiomics for Predicting the Aggressiveness of Papillary Thyroid Carcinoma Using Hyperspectral Images.Proceedings of SPIE--the International Society for Optical Engineering · 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
- Pixel-level Tumor Margin Assessment of Surgical Specimen with Hyperspectral Imaging and Deep Learning Classification.Proceedings of SPIE--the International Society for Optical Engineering · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
For patients undergoing surgical cancer resection of squamous cell carcinoma (SCCa), cancer-free surgical margins are essential for good prognosis. We developed a method to use hyperspectral imaging (HSI), a noncontact optical imaging modality, and convolutional neural networks (CNNs) to perform an optical biopsy of ex-vivo, surgical gross-tissue specimens, collected from 21 patients undergoing surgical cancer resection. Using a cross-validation paradigm with data from different patients, the CNN can distinguish SCCa from normal aerodigestive tract tissues with an area under the receiver operator curve (AUC) of 0.82. Additionally, normal tissue from the upper aerodigestive tract can be subclassified into squamous epithelium, muscle, and gland with an average AUC of 0.94. After separately training on thyroid tissue, the CNN can differentiate between thyroid carcinoma and normal thyroid with an AUC of 0.95, 92% accuracy, 92% sensitivity, and 92% specificity. Moreover, the CNN can discriminate medullary thyroid carcinoma from benign multinodular goiter (MNG) with an AUC of 0.93. Classical-type papillary thyroid carcinoma is differentiated from MNG with an AUC of 0.91. Our preliminary results demonstrate that an HSI-based optical biopsy method using CNNs can provide multicategory diagnostic information for normal and cancerous head-and-neck tissue, and more patient data are needed to fully investigate the potential and reliability of the proposed technique.
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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.