ArticleJournal of clinical medicine2021
Gallbladder Polyp Classification in Ultrasound Images Using an Ensemble Convolutional Neural Network Model.
Article in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Review
- An integrative deep learning model based on dual-mode ultrasound for diagnosing gallbladder polyps.Insights into imaging · 2026Article
- GBCapsNet: A calibrated capsule network for automated gallbladder disease diagnosis via ultrasound imaging.PloS one · 2026Article
- Development of a preoperative prediction model for neoplastic polyps of the gallbladder based on a convolutional neural network model using ultrasonic images.Translational gastroenterology and hepatology · 2026Article
- Diagnostic performance of real-time artificial intelligence using deep learning analysis of endoscopic ultrasound videos for gallbladder polypoid lesions.Scientific reports · 2025Article
- MSFE-GallNet-X: a multi-scale feature extraction-based CNN Model for gallbladder disease analysis with enhanced explainability.BMC medical imaging · 2025Article
- Artificial intelligence in abdominal and pelvic ultrasound imaging: current applications.Abdominal radiology (New York) · 2025Review
- Establishing a radiomics model using contrast-enhanced ultrasound for preoperative prediction of neoplastic gallbladder polyps exceeding 10 mm.European journal of medical research · 2025Article
- Predicting Neoplastic Gallbladder Polyps: The Role of Current Surgical Indications and Preoperative Images.The Korean journal of gastroenterology = Taehan Sohwagi Hakhoe chi · 2025Article
- Enhanced gallbladder cancer detection via active and self-supervised learning integration: Innovating B-ultrasound image analysis.PloS one · 2025Article
- Current status of artificial intelligence analysis for the diagnosis of gallbladder diseases using ultrasonography: a scoping review.Translational gastroenterology and hepatology · 2025Review
- Advances in the management of gallbladder polyps: establishment of predictive models and the rise of gallbladder-preserving polypectomy procedures.BMC gastroenterology · 2024Review
- Diagnosing gangrenous cholecystitis on computed tomography using deep learning: A preliminary study.Acute medicine & surgeryArticle
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Authors and funding
6 authors.
Funding
Abstract
Differential diagnosis of true gallbladder polyps remains a challenging task. This study aimed to differentiate true polyps in ultrasound images using deep learning, especially gallbladder polyps less than 20 mm in size, where clinical distinction is necessary. A total of 501 patients with gallbladder polyp pathology confirmed through cholecystectomy were enrolled from two tertiary hospitals. Abdominal ultrasound images of gallbladder polyps from these patients were analyzed using an ensemble model combining three convolutional neural network (CNN) models and a 5-fold cross-validation. True polyp diagnosis with the ensemble model that learned only using ultrasonography images achieved an area under receiver operating characteristic curve (AUC) of 0.8960 and accuracy of 83.63%. After adding patient age and polyp size information, the diagnostic performance of the ensemble model improved, with a high specificity of 88.35%, AUC of 0.9082, and accuracy of 87.61%, outperforming the individual CNN models constituting the ensemble model. In the subgroup analysis, the ensemble model showed the best performance with AUC of 0.9131 for polyps larger than 10 mm. Our proposed ensemble model that combines three CNN models classifies gallbladder polyps of less than 20 mm in ultrasonography images with high accuracy and can be useful for avoiding unnecessary cholecystectomy with high specificity.
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