Filters








4 Hits in 3.5 sec

CS2-Net: Deep Learning Segmentation of Curvilinear Structures in Medical Imaging [article]

Lei Mou, Yitian Zhao, Huazhu Fu, Yonghuai Liu, Jun Cheng, Yalin Zheng, Pan Su, Jianlong Yang, Li Chen, Alejandro F Frang, Masahiro Akiba, Jiang Liu
2020 arXiv   pre-print
We introduce a new curvilinear structure segmentation network (CS2-Net), which includes a self-attention mechanism in the encoder and decoder to learn rich hierarchical representations of curvilinear structures  ...  In this work, we propose a generic and unified convolution neural network for the segmentation of curvilinear structures and illustrate in several 2D/3D medical imaging modalities.  ...  In this work, we carefully designed a network focusing on the extraction of the curvilinear structures in medical images.  ... 
arXiv:2010.07486v2 fatcat:jfieuh5tqrdannpiqwqpclacea

CS2-Net: Deep Learning Segmentation of Curvilinear Structures in Medical Imaging

Lei Mou, Yitian Zhao, Huazhu Fu, Yonghuai Liux, Jun Cheng, Yalin Zheng, Pan Su, Jianlong Yang, Li Chen, Alejandro F Frangi, Masahiro Akiba, Jiang Liu
2020 Medical Image Analysis  
We introduce a new curvilinear structure segmentation network (CS2-Net), which includes a self-attention mechanism in the encoder and decoder to learn rich hierarchical representations of curvilinear structures  ...  In this work, we propose a generic and unified convolution neural network for the segmentation of curvilinear structures and illustrate in several 2D/3D medical imaging modalities.  ...  In this work, we propose a general unified convolutionary neural network for curvilinear structure segmentation of images in various 2D/3D medical imaging modalities.  ... 
doi:10.1016/j.media.2020.101874 pmid:33166771 fatcat:45ud25vwyfhkdmihddossl6l5e

RA V-Net: Deep learning network for automated liver segmentation [article]

Zhiqi Lee, Sumin Qi, Chongchong Fan, Ziwei Xie
2021 arXiv   pre-print
In recent years, automated processing of medical images has gained breakthroughs.  ...  In this paper, we propose RA V-Net, which is an improved medical image automatic segmentation model based on U-Net. It has the following three main innovations.  ...  Conclusion This simulation experiment demonstrates the difference in performance of deep learning models when applied to medical image segmentation and finds several directions to optimize the automated  ... 
arXiv:2112.08232v2 fatcat:vq4o7jmdw5heteo5cdk4ijd4ce

CAS-Net: A Novel Coronary Artery Segmentation Neural Network

Rawaa Hamdi, Asma Kerkeni, Mouhamed hédi Bedoui, Asma Ben Abdallah
2021 ESANN 2021 proceedings   unpublished
In conventional X-ray coronary angiography, accurate coronary artery segmentation is a crucial and challenging step in the assessment of coronary artery disease.  ...  In this paper, we propose a new architecture (CAS-Net) for coronary artery segmentation.  ...  [9] , proposed the Cs2-Net, a neural network for curvilinear structure segmentation.  ... 
doi:10.14428/esann/2021.es2021-157 fatcat:yu77ufnz3rgsndfuk36axkcat4