ArticleJournal of imaging2022
Training Ultrasound Image Classification Deep-Learning Algorithms for Pneumothorax Detection Using a Synthetic Tissue Phantom Apparatus.
Article in Journal of imaging, 2022. 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.
- Role of artificial intelligence and point of care ultrasound in management of critically ill patients.World journal of critical care medicine · 2026Review
- A Diagnostic Algorithm for Reconstructing the Direction of Gunshots Using OsiriX and Maya in Living Patients: A Forensic Radiology Approach.Diagnostics (Basel, Switzerland) · 2026Article
- Artificial Intelligence-Assisted Lung Ultrasound for Pneumothorax: Diagnostic Accuracy Compared with CT in Emergency and Critical Care.Tomography (Ann Arbor, Mich.) · 2025Article
- Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would.Frontiers in physiology · 2025Article
- Overview of Wearable Healthcare Devices for Clinical Decision Support in the Prehospital Setting.Sensors (Basel, Switzerland) · 2024Review
- Evaluation of Deep Learning Model Architectures for Point-of-Care Ultrasound Diagnostics.Bioengineering (Basel, Switzerland) · 2024Article
- Design and testing of ultrasound probe adapters for a robotic imaging platform.Scientific reports · 2024Article
- Development of an Artificial Soft Solid Gel Using Gelatin Material for High-Quality Ultrasound Diagnosis.Diagnostics (Basel, Switzerland) · 2024Article
- Quantitative assessment of pneumothorax by using Shannon entropy of lung ultrasound M-mode image and diaphragmatic excursion based on automated measurement.Quantitative imaging in medicine and surgery · 2024Article
- Using Ultrasound Image Augmentation and Ensemble Predictions to Prevent Machine-Learning Model Overfitting.Diagnostics (Basel, Switzerland) · 2023Article
- An extended focused assessment with sonography in trauma ultrasound tissue-mimicking phantom for developing automated diagnostic technologies.Frontiers in bioengineering and biotechnology · 2023Article
- Using an Ultrasound Tissue Phantom Model for Hybrid Training of Deep Learning Models for Shrapnel Detection.Journal of imaging · 2022Article
- Evaluation of an Object Detection Algorithm for Shrapnel and Development of a Triage Tool to Determine Injury Severity.Journal of imaging · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Ultrasound (US) imaging is a critical tool in emergency and military medicine because of its portability and immediate nature. However, proper image interpretation requires skill, limiting its utility in remote applications for conditions such as pneumothorax (PTX) which requires rapid intervention. Artificial intelligence has the potential to automate ultrasound image analysis for various pathophysiological conditions. Training models require large data sets and a means of troubleshooting in real-time for ultrasound integration deployment, and they also require large animal models or clinical testing. Here, we detail the development of a dynamic synthetic tissue phantom model for PTX and its use in training image classification algorithms. The model comprises a synthetic gelatin phantom cast in a custom 3D-printed rib mold and a lung mimicking phantom. When compared to PTX images acquired in swine, images from the phantom were similar in both PTX negative and positive mimicking scenarios. We then used a deep learning image classification algorithm, which we previously developed for shrapnel detection, to accurately predict the presence of PTX in swine images by only training on phantom image sets, highlighting the utility for a tissue phantom for AI applications.
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