YOLOv11-MFF: A multi-scale frequency-adaptive fusion network for enhanced CXR anomaly detection

Chest X-ray (CXR) represents one of the most widely utilized clinical diagnostic tools for thoracic diseases. Nevertheless, computer-aided diagnosis based on chest radiographs still faces considerable challenges in anomaly detection. Certain lesions in CXRs exhibit subtle radiographic characteristic...

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Vydané v:	PloS one Ročník 20; číslo 10; s. e0334283
Hlavní autori:	Guan, Li, Zhang, Ruting, Zhao, Yi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Public Library of Science 01.10.2025 Public Library of Science (PLoS)
Predmet:	Algorithms Anomalies Background noise Chest Classification Datasets Deep learning Disease Fourier transforms Humans Lesions Localization Modules Neural networks Neural Networks, Computer Pneumonia Radiographic Image Interpretation, Computer-Assisted - methods Radiography, Thoracic - methods Semantics Thorax
ISSN:	1932-6203, 1932-6203
On-line prístup:	Získať plný text
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