Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would
IntroductionEmergency rescue scenes and pre-hospital emergency stages commonly encounter trauma victims. Life-saving measures must be taken at the scene if a trauma patient has pneumothorax; if the patient is not evaluated and diagnosed right away, their life may be in jeopardy. Ultrasound, which ha...
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Frontiers Media S.A.
2025-05-01
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| Series: | Frontiers in Physiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphys.2025.1530808/full |
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| author | Xiaoyong Qiang Qiang Wang Guanjun Liu Limei Song Weibin Zhou Ming Yu Hang Wu Hang Wu |
| author_facet | Xiaoyong Qiang Qiang Wang Guanjun Liu Limei Song Weibin Zhou Ming Yu Hang Wu Hang Wu |
| author_sort | Xiaoyong Qiang |
| collection | DOAJ |
| description | IntroductionEmergency rescue scenes and pre-hospital emergency stages commonly encounter trauma victims. Life-saving measures must be taken at the scene if a trauma patient has pneumothorax; if the patient is not evaluated and diagnosed right away, their life may be in jeopardy. Ultrasound, which has the advantages of being non-invasive, non-radioactive, portable, rapid, and repeatable, can be used to diagnose pneumothorax. However, those who interpret ultrasound images must undergo extensive, specialized, and rigorous training. Deep learning technology allows for the intelligent diagnosis of ultrasound images, allowing general healthcare professionals to quickly and with minimal training diagnose pneumothorax in lung ultrasound patients.MethodsPrevious studies focused primarily on the lung-sliding characteristics of M-mode images, neglecting other key features in lung ultrasonography pneumothorax, and used similar technological techniques. Our study team used video understanding technology for medical ultrasound imaging diagnostics, training the TSM video understanding model on the ResNet50 network with 657 clips and testing the model with untrained 164 lung ultrasound clips.ResultsThe model’s sensitivity was 99.21%, specificity was 89.19%, and average accuracy was 96.95%. The F1 score was 0.929, and the AUC was 0.97.DiscussionThis study is the first to apply video understanding models to the multi-feature fusion diagnosis of pneumothorax, demonstrating the feasibility of using video understanding technology in medical image diagnosis. |
| format | Article |
| id | doaj-art-ff4710fed94c40f89eadfc4c32adad67 |
| institution | Kabale University |
| issn | 1664-042X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Physiology |
| spelling | doaj-art-ff4710fed94c40f89eadfc4c32adad672025-08-20T03:48:28ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2025-05-011610.3389/fphys.2025.15308081530808Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor wouldXiaoyong Qiang0Qiang Wang1Guanjun Liu2Limei Song3Weibin Zhou4Ming Yu5Hang Wu6Hang Wu7College of Electronic Information and Automation, Tianjin University of Science and Technology, Tianjin, ChinaCollege of Electronic Information and Automation, Tianjin University of Science and Technology, Tianjin, ChinaSystems Engineering Institute, Academy of Military Sciences, People’s Liberation Army, Tianjin, ChinaSystems Engineering Institute, Academy of Military Sciences, People’s Liberation Army, Tianjin, ChinaCollege of Electronic Information and Automation, Tianjin University of Science and Technology, Tianjin, ChinaSystems Engineering Institute, Academy of Military Sciences, People’s Liberation Army, Tianjin, ChinaSystems Engineering Institute, Academy of Military Sciences, People’s Liberation Army, Tianjin, ChinaSchool of Artificial Intelligence, Nankai University, Tianjin, ChinaIntroductionEmergency rescue scenes and pre-hospital emergency stages commonly encounter trauma victims. Life-saving measures must be taken at the scene if a trauma patient has pneumothorax; if the patient is not evaluated and diagnosed right away, their life may be in jeopardy. Ultrasound, which has the advantages of being non-invasive, non-radioactive, portable, rapid, and repeatable, can be used to diagnose pneumothorax. However, those who interpret ultrasound images must undergo extensive, specialized, and rigorous training. Deep learning technology allows for the intelligent diagnosis of ultrasound images, allowing general healthcare professionals to quickly and with minimal training diagnose pneumothorax in lung ultrasound patients.MethodsPrevious studies focused primarily on the lung-sliding characteristics of M-mode images, neglecting other key features in lung ultrasonography pneumothorax, and used similar technological techniques. Our study team used video understanding technology for medical ultrasound imaging diagnostics, training the TSM video understanding model on the ResNet50 network with 657 clips and testing the model with untrained 164 lung ultrasound clips.ResultsThe model’s sensitivity was 99.21%, specificity was 89.19%, and average accuracy was 96.95%. The F1 score was 0.929, and the AUC was 0.97.DiscussionThis study is the first to apply video understanding models to the multi-feature fusion diagnosis of pneumothorax, demonstrating the feasibility of using video understanding technology in medical image diagnosis.https://www.frontiersin.org/articles/10.3389/fphys.2025.1530808/fullpneumothoraxlung ultrasoundmedical imagingintelligent diagnosticsdeep learningvideo understanding |
| spellingShingle | Xiaoyong Qiang Qiang Wang Guanjun Liu Limei Song Weibin Zhou Ming Yu Hang Wu Hang Wu Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would Frontiers in Physiology pneumothorax lung ultrasound medical imaging intelligent diagnostics deep learning video understanding |
| title | Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would |
| title_full | Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would |
| title_fullStr | Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would |
| title_full_unstemmed | Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would |
| title_short | Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would |
| title_sort | use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would |
| topic | pneumothorax lung ultrasound medical imaging intelligent diagnostics deep learning video understanding |
| url | https://www.frontiersin.org/articles/10.3389/fphys.2025.1530808/full |
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