ArticleCancers2021
Hyperspectral Imaging Combined with Artificial Intelligence in the Early Detection of Esophageal Cancer.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 3 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
49 citing papers in PubMed, 3 syntheses or guidelines pooled it, 92 citations in OpenAlex.
- Medical hyperspectral imaging: an updated review of technology advancements and biomedical applications.Journal of biomedical optics · 2026Pooled it
- Clinical applications of hyperspectral imaging in gastroenterology and hepatology: A systematic review.Indian journal of gastroenterology : official journal of the Indian Society of Gastroenterology · 2026Pooled it
- Recent Advances in Counterfeit Art, Document, Photo, Hologram, and Currency Detection Using Hyperspectral Imaging.Sensors (Basel, Switzerland) · 2022Pooled it
- AI-Powered TAT-Net Hyperspectral Imaging for Rapid and Accurate Differentiation of Sinonasal Inverted Papilloma and Malignancy.World journal of otorhinolaryngology - head and neck surgery · 2026Article
- Hyperspectral imaging system for multiplexed cancer marker detection: design and clinical evaluation.Journal of biomedical optics · 2026Article
- Enhancing esophageal cancer detection using a deep learning framework and a novel spectrum-aided vision enhancer for virtual narrow band imaging.Scientific reports · 2026Article
- Hyperspectral reconstruction of white light endoscopy images for enhanced segmentation of early esophageal lesions in patients.iScience · 2026Article
- Advances and Opportunities in NIR-II Endoscopy: From Diagnosis to Therapeutic Applications.Diagnostics (Basel, Switzerland) · 2026Review
- Classification of esophageal cancer by using hyperspectral data.International journal of computer assisted radiology and surgery · 2026Article
- Explainable machine learning for early diagnosis of esophageal cancer: A feature-enriched Light Gradient Boosting Machine framework with Shapley Additive Explanations and Local Interpretable Model-Agnostic Explanations interpretations.The Journal of international medical research · 2026Article
- Hyperspectral imaging for intraoperative brain tumor identification through fusion of spectral, textural, and spectral index features.PloS one · 2026Article
- Computational Approach Improves Diagnostic Performance Based on Tumor-Associated Autoantibodies in Esophageal Squamous Cell Carcinoma.Computational and structural biotechnology journal · 2026Article
- Transforming Endoscopic Image Classification with Spectrum-Aided Vision for Early and Accurate Cancer Identification.Diagnostics (Basel, Switzerland) · 2025Article
- Enhancing Early GI Disease Detection with Spectral Visualization and Deep Learning.Bioengineering (Basel, Switzerland) · 2025Article
- Software-Based Transformation of White Light Endoscopy Images to Hyperspectral Images for Improved Gastrointestinal Disease Detection.Diagnostics (Basel, Switzerland) · 2025Article
- Deep learning detected histological differences between invasive and non-invasive areas of early esophageal cancer.Cancer science · 2025Article
- Small intestinal bleeding prediction by spectral reconstruction through band selection.Journal of biomedical optics · 2025Article
- The Evolving Landscape of Cervical Cancer: Breakthroughs in Screening and Therapy Through Integrating Biotechnology and Artificial Intelligence.Molecular biotechnology · 2025Review
- Sine oculis homeobox homolog family function in gastrointestinal cancer: Progression and comprehensive analysis.World journal of clinical oncology · 2025Review
- Precision Imaging for Early Detection of Esophageal Cancer.Bioengineering (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
Abstract
This study uses hyperspectral imaging (HSI) and a deep learning diagnosis model that can identify the stage of esophageal cancer and mark the locations. This model simulates the spectrum data from the image using an algorithm developed in this study which is combined with deep learning for the classification and diagnosis of esophageal cancer using a single-shot multibox detector (SSD)-based identification system. Some 155 white-light endoscopic images and 153 narrow-band endoscopic images of esophageal cancer were used to evaluate the prediction model. The algorithm took 19 s to predict the results of 308 test images and the accuracy of the test results of the WLI and NBI esophageal cancer was 88 and 91%, respectively, when using the spectral data. Compared with RGB images, the accuracy of the WLI was 83% and the NBI was 86%. In this study, the accuracy of the WLI and NBI was increased by 5%, confirming that the prediction accuracy of the HSI detection method is significantly improved.
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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.