ArticleCancers2022
Intelligent Identification of Early Esophageal Cancer by Band-Selective Hyperspectral Imaging.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 3 of them syntheses that pooled it.
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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.
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Who cites it
29 citing papers in PubMed, 3 syntheses or guidelines pooled it, 67 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
- Enhancing esophageal cancer detection using a deep learning framework and a novel spectrum-aided vision enhancer for virtual narrow band imaging.Scientific reports · 2026Article
- Perspective on the current state of hyperspectral/multispectral imaging for minimally invasive surgery.Journal of biomedical optics · 2026Review
- Building an interpretable machine learning prognosis prediction model-based on baseline examinations of patients with esophageal cancer undergoing surgery.Frontiers in oncology · 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
- Nomographic predictive models for complications after minimally invasive esophagectomy: Current status and future perspectives.World journal of gastrointestinal surgery · 2025Review
- Spectral Analysis of Extrahepatic Bile Ducts During Normothermic Liver Machine Perfusion.Bioengineering (Basel, Switzerland) · 2025Article
- Current Role of Artificial Intelligence in the Management of Esophageal Cancer.Journal of clinical medicine · 2025Review
- Small intestinal bleeding prediction by spectral reconstruction through band selection.Journal of biomedical optics · 2025Article
- 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
- Advancements in Hyperspectral Imaging and Computer-Aided Diagnostic Methods for the Enhanced Detection and Diagnosis of Head and Neck Cancer.Biomedicines · 2024Review
- Spectrum aided vision enhancer enhances mucosal visualization by hyperspectral imaging in capsule endoscopy.Scientific reports · 2024Article
- Technological Frontiers in Brain Cancer: A Systematic Review and Meta-Analysis of Hyperspectral Imaging in Computer-Aided Diagnosis Systems.Diagnostics (Basel, Switzerland) · 2024Review
- Assessing the Efficacy of the Spectrum-Aided Vision Enhancer (SAVE) to Detect Acral Lentiginous Melanoma, Melanoma In Situ, Nodular Melanoma, and Superficial Spreading Melanoma.Diagnostics (Basel, Switzerland) · 2024Article
- Evaluation of Spectrum-Aided Visual Enhancer (SAVE) in Esophageal Cancer Detection Using YOLO Frameworks.Diagnostics (Basel, Switzerland) · 2024Article
- Handheld hyperspectral imaging as a tool for the post-mortem interval estimation of human skeletal remains.Heliyon · 2024Article
- Design of risk prediction model for esophageal cancer based on machine learning approach.Heliyon · 2024Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
Abstract
In this study, the combination of hyperspectral imaging (HSI) technology and band selection was coupled with color reproduction. The white-light images (WLIs) were simulated as narrow-band endoscopic images (NBIs). As a result, the blood vessel features in the endoscopic image became more noticeable, and the prediction performance was improved. In addition, a single-shot multi-box detector model for predicting the stage and location of esophageal cancer was developed to evaluate the results. A total of 1780 esophageal cancer images, including 845 WLIs and 935 NBIs, were used in this study. The images were divided into three stages based on the pathological features of esophageal cancer: normal, dysplasia, and squamous cell carcinoma. The results showed that the mean average precision (mAP) reached 80% in WLIs, 85% in NBIs, and 84% in HSI images. This study's results showed that HSI has more spectral features than white-light imagery, and it improves accuracy by about 5% and matches the results of NBI predictions.
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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.