Pulmonary Textures Classification via a Multi-Scale Attention Network

Precise classification of pulmonary textures is crucial to develop a computer aided diagnosis (CAD) system of diffuse lung diseases (DLDs). Although deep learning techniques have been applied to this task, the classification performance is not satisfied for clinical requirements, since commonly-used...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics 2020-07, Vol.24 (7), p.2041-2052
Hauptverfasser:	Xu, Rui, Cong, Zhen, Ye, Xinchen, Hirano, Yasushi, Kido, Shoji, Gyobu, Tomoko, Kawata, Yutaka, Honda, Osamu, Tomiyama, Noriyuki
Format:	Artikel
Sprache:	eng
Schlagworte:	Attention Classification Computed tomography computer-aided diagnosis Deep Learning deep network diffuse lung diseases Humans Image classification Image Interpretation, Computer-Assisted - methods Image Processing, Computer-Assisted Image resolution Lung Lung - anatomy & histology Lung - diagnostic imaging Lung diseases Lung Diseases - diagnostic imaging Lung Diseases - pathology Machine learning Medical diagnosis Modules multi-scale Network architecture network visualization pulmonary textures classification Representations Solid modeling Task analysis Tomography, X-Ray Computed Visualization
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