Chest X-ray pneumothorax segmentation using U-Net with EfficientNet and ResNet architectures

Medical imaging refers to visualization techniques to provide valuable information about the internal structures of the human body for clinical applications, diagnosis, treatment, and scientific research. Segmentation is one of the primary methods for analyzing and processing medical images, which h...

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Bibliographic Details
Published in:	PeerJ. Computer science Vol. 7; p. e607
Main Authors:	Abedalla, Ayat, Abdullah, Malak, Al-Ayyoub, Mahmoud, Benkhelifa, Elhadj
Format:	Journal Article
Language:	English
Published:	United States PeerJ. Ltd 29.06.2021 PeerJ, Inc PeerJ Inc
Subjects:	Algorithms Algorithms and Analysis of Algorithms Artificial Intelligence Artificial neural networks Bioinformatics Brain research Cable television broadcasting industry Chest tubes Coders Computational linguistics Computer networks Data augmentation Data mining Data Mining and Machine Learning Datasets Deep learning Encoders-Decoders Image processing Image segmentation Language processing Lungs Machine learning Magnetic resonance imaging Medical image segmentation Medical imaging Medical imaging equipment Medical research Natural language interfaces Neural networks Physicians Pneumothorax Radiation ResNet-50 SE-ResNext-50 Semantic segmentation Semantics Success Technology application Test-time augmentation Testing time Training U-Net Ultrasonic imaging X-rays United States Pneumothorax EfficientNet-B4 Test-time augmentation Transfer learning ResNet-50 U-Net Medical image segmentation SE-ResNext-50
ISSN:	2376-5992, 2376-5992
Online Access:	Get full text
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