LMA-Net: Lightweight Multiple Attention Network for Multi-Source Heterogeneous Pulmonary CXR Segmentation

The automatic pulmonary segmentation for chest X-ray(CXR) plays an important role in assisting diagnosis. Many deep learning methods have the problems of high computational complexity and low segmentation accuracy, which hinder the application to clinical workstations. Therefore, this paper proposes...

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Veröffentlicht in:	IEEE access 2024, Vol.12, p.72912-72923
Hauptverfasser:	Mamut, Turghunjan, Meng, Lun, Pei, Ziyi, Weng, Tengfei, Han, Qi, Wu, Kepeng, Qian, Xin, Xu, Hongxiang, Qiu, Zicheng, Tian, Yuan, Pei, Yangjun
Format:	Artikel
Sprache:	eng
Schlagworte:	attention Biomedical imaging Convolutional neural network Convolutional neural networks Datasets Decoding Deep learning Floating point arithmetic Heterogeneous networks Image segmentation Lightweight Lungs Medical diagnosis medical image segmentation Metric space multi-source heterogeneous dataset Pulmonology Segmentation Task analysis Weight reduction
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