ArticleJournal of biomedical optics2017
Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging.
Article in Journal of biomedical optics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04589884 (Intraoperative EXamination Using MAChine-learning-based HYperspectral for diagNosis & Autonomous Anatomy Assessment), which is not on this map. Cited by 85 papers, 2 of them syntheses 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.
Intraoperative EXamination Using MAChine-learning-based HYperspectral for diagNosis & Autonomous Anatomy Assessment
Who cites it
85 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
- Current role of artificial intelligence in head and neck cancer surgery: a systematic review of literature.Exploration of targeted anti-tumor therapy · 2023Pooled it
- Role of artificial intelligence in head and neck surgery - A narrative review.Turkish journal of surgery · 2026Article
- Neural illumination calibration for surgical workflow-optimized spectral imaging.International journal of computer assisted radiology and surgery · 2026Article
- The transformative impact of artificial intelligence on periodontal care: A review.Bioinformation · 2026Article
- USSGAN: Unsupervised Spectral and Spatial Attention-Based Generative Adversarial Network for Cholangiocarcinoma Detection.Chemical & biomedical imaging · 2025Article
- From Innovation to Application: Can Emerging Imaging Techniques Transform Breast Cancer Diagnosis?Diagnostics (Basel, Switzerland) · 2025Review
- Critical review of patient outcome study in head and neck cancer radiotherapy.Meta-radiology · 2025Article
- Toward real-time margin assessment in breast-conserving surgery with hyperspectral imaging.Scientific reports · 2025Article
- Article
- Assessing the Reporting Quality of Machine Learning Algorithms in Head and Neck Oncology.The Laryngoscope · 2025Article
- Optimization of Transfer Learning of Foundation Models for Hyperspectral Histologic Imaging.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- Liquid biopsy in cancer diagnosis and prognosis: a paradigm shift in precision oncology.Frontiers in molecular biosciences · 2025Review
- Advancements in Hyperspectral Imaging and Computer-Aided Diagnostic Methods for the Enhanced Detection and Diagnosis of Head and Neck Cancer.Biomedicines · 2024Review
- Fluorescence excitation-scanning hyperspectral imaging with scalable 2D-3D deep learning framework for colorectal cancer detection.Scientific reports · 2024Article
- 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
- Artificial Intelligence for Image Analysis in Oral Squamous Cell Carcinoma: A Review.Diagnostics (Basel, Switzerland) · 2023Review
- Gender, Smoking History, and Age Prediction from Laryngeal Images.Journal of imaging · 2023Article
- Artificial Intelligence in Medicine and Dentistry.Acta stomatologica Croatica · 2023Review
- Deep Learning in Medical Hyperspectral Images: A Review.Sensors (Basel, Switzerland) · 2022Review
25 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Surgical cancer resection requires an accurate and timely diagnosis of the cancer margins in order to achieve successful patient remission. Hyperspectral imaging (HSI) has emerged as a useful, noncontact technique for acquiring spectral and optical properties of tissue. A convolutional neural network (CNN) classifier is developed to classify excised, squamous-cell carcinoma, thyroid cancer, and normal head and neck tissue samples using HSI. The CNN classification was validated by the manual annotation of a pathologist specialized in head and neck cancer. The preliminary results of 50 patients indicate the potential of HSI and deep learning for automatic tissue-labeling of surgical specimens of head and neck patients.
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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.