Spontaneous Pneumothorax Detection in Chest X‑rays using Convolutional Neural Networks
- سال انتشار: 1404
- محل انتشار: InfoScience Trends، دوره: 2، شماره: 5
- کد COI اختصاصی: JR_ISJTREND-2-5_002
- زبان مقاله: انگلیسی
- تعداد مشاهده: 6
نویسندگان
Faculty of Medicine, Gorgan University of Medical Sciences, Gorgan, Iran.
Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
General Surgery Department, Shiraz University of Medical Sciences, Shiraz, Iran.
Faculty of Medicine, Kurdistan University of Medical Sciences, Kurdistan, Iran.
General Surgery Department, Tehran University of Medical Sciences, Tehran, Iran.
Faculty of Medicine, Jahrom University of Medical Sciences, Jahrom, Iran.
Faculty of Medicine, Tehran Islamic Azad University of Medical Sciences, Tehran, Iran.
Internal Medicine Department, Islamic Azad University of Medical Sciences, Tehran, Iran.
چکیده
This paper evaluates the application of Convolutional Neural Networks (CNNs) for detecting spontaneous pneumothorax in chest X-rays. For this study, we randomly selected ۲۰۰۰ chest X-ray images with pneumothorax from the publicly available National Institutes of Health (NIH) database, which were subsequently allocated to training and testing datasets. To enhance the model's generalization, the images were preprocessed by normalizing, resizing, and augmenting the dataset. The proposed CNN model includes multiple convolutional layers that extract low-level features, followed by max-pooling layers for progressive dimensionality reduction. To combine the extracted features and make predictions, fully connected layers are employed, and a hyperbolic tangent (tanh) activation function is used in the output layer for binary classification. The Adam optimizer is utilized to train the model, and its performance is assessed using standard performance metrics, including accuracy, precision, sensitivity, specificity, and specificity. The results show that the developed CNN-based method outperforms conventional approaches based on machine learning, such as Decision Tree, Random Forest, and SVM.کلیدواژه ها
Pneumothorax, Neural Networks, computer, Radiography, Deep Learning, Diagnostic Imagingاطلاعات بیشتر در مورد COI
COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.
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