Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 89-94.doi: 10.11896/jsjkx.201000116

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Comparative Study on Classification and Recognition of Medical Images Using Deep Learning Network

LIU Han-qing1, KANG Xiao-dong1, LI Bo2, ZHANG Hua-li1, FENG Ji-chao1, HAN Jun-ling1   

  1. 1 School of Medical Image,Tianjin Medical University,Tianjin 300202,China
    2 Tianjin Third Central Hospital,Tianjin 300171,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:LIU Han-qing,born in 1997,M.S.candidate.His main research interest includes medical image processing and so on.
    KANG Xiao-dong,born in 1964,Ph.D,professor.His main research interests include medical image processing and medical information system integration.
  • Supported by:
    Beijing-Tianjin-Hebei Collaborative Innovation Project(17YEXTZC00020).

Abstract: Computer-aided diagnosis technology has practical significance in clinical medicine.The images of lung nodules and articulatio coxae fractures are used as typical regional and boundary feature images to discuss their applicability in different networks.First,the CT images of the lung nodules and the X-ray fracture images of the articulatio coxae are labeled,and they are pre-trained with CNN,Resnet,DBN and SGAN and fine-tuned,and the classification and recognition are completed via the Softmax classifier.Secondly,the image spatial resolution and noise are used as the comparative characteristics of different deep lear-ning networks,and the recognition rate is analyzed from the aspects of deep learning network structures.The simulation experiment results show that Resnet performs preeminently in all data sets,and has striking generalization ability and robustness.

Key words: CNN, DBN, Deep learning, Images classification, Resnet, SGAN

CLC Number: 

  • TP391
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