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Femoral head segmentation based on improved fully convolutional neural network for ultrasound images

文献类型：期刊论文

作者Chen, Lei1; Cui, Yutao1; Song, Hong1; Huang, Bingxuan2; Yang, Jian3; Zhao, Di4; Xia, Bei2
刊名SIGNAL IMAGE AND VIDEO PROCESSING
出版日期2020-07-01
卷号14期号:5页码:1043-1051
关键词Developmental dysplasia of the hip Femoral head segmentation Fully convolutional neural networks Feature visualization
ISSN号1863-1703
DOI10.1007/s11760-020-01637-z
英文摘要Developmental dysplasia of the hip is a medical term representing the hip joint instability that appears mainly in infants. The assessment metric of physician is based on the femoral head coverage rate, which needs to segment the femoral head area in 2D ultrasound images. In this paper, we propose an approach to automatically segment the femoral head. The proposed method consists of two parts, firstly, mean filtering, morphological processing and least squares operation are used to detect the ilium and acetabular bone baseline to coarsely obtain the region of interest of the femoral head, then followed by an improved fully convolutional neural network named FNet which integrates the convolution encoder-decoder architecture, pooling indices and residual connection operation for more accurate segmentation. FNet is trained in a cascaded way, which can help the network learn more features with a limited dataset and thus further improve the segmentation performance. Experimental results show that the proposed method achieved an average dice, recall and IoU value of 0.946, 0.937 and 0.897. Moreover, the features learned by convolutional layers are visualized to demonstrate that FNet can focus on significant features, which is helpful to restore the contour of the femoral head more precisely. In conclusion, the proposed method is capable of segmenting femoral head accurately and guiding the diagnosis of developmental dysplasia of the hip.
WOS研究方向Engineering ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000537827700022
出版者SPRINGER LONDON LTD
源URL[http://119.78.100.204/handle/2XEOYT63/15241]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Song, Hong
作者单位1.Beijing Inst Technol, Sch Comp Sci & Technol, Beijing 100081, Peoples R China
2.Shenzhen Childrens Hosp, Shenzhen 518038, Peoples R China
3.Beijing Inst Technol, Sch Opt & Elect, Beijing 100081, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Lei,Cui, Yutao,Song, Hong,et al. Femoral head segmentation based on improved fully convolutional neural network for ultrasound images[J]. SIGNAL IMAGE AND VIDEO PROCESSING,2020,14(5):1043-1051.
APA Chen, Lei.,Cui, Yutao.,Song, Hong.,Huang, Bingxuan.,Yang, Jian.,...&Xia, Bei.(2020).Femoral head segmentation based on improved fully convolutional neural network for ultrasound images.SIGNAL IMAGE AND VIDEO PROCESSING,14(5),1043-1051.
MLA Chen, Lei,et al."Femoral head segmentation based on improved fully convolutional neural network for ultrasound images".SIGNAL IMAGE AND VIDEO PROCESSING 14.5(2020):1043-1051.

入库方式： OAI收割

来源：计算技术研究所

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