Radiology report generation via visual-semantic ambivalence-aware network and focal self-critical sequence training

Radiology report generation, which aims to provide accurate descriptions of both normal and abnormal regions, has been attracting growing research attention. Recently, despite considerable progress, data-driven deep-learning based models still face challenges in capturing and describing the abnormal...

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Veröffentlicht in:	Neural networks Jg. 194; S. 108102
Hauptverfasser:	Yi, Xiulong, Fu, You, Bi, Enxu, Liang, Jianguo, Zhang, Hao, Yu, Jianzhi, Li, Qianqian, Hua, Rong, Wang, Rui
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Ltd 01.02.2026
Schlagworte:	Image caption Radiology report generation Reinforcement learning Transformer Image caption Transformer Radiology report generation Reinforcement learning
ISSN:	0893-6080, 1879-2782, 1879-2782
Online-Zugang:	Volltext
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