Discriminating between benign and malignant breast tumors using 3D convolutional neural network in dynamic contrast enhanced-MR images

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 10138, Issue , 2017, Pages

  Li, Jing ^a   Fan, Ming ^a   Zhang, Juan ^b   Li, Lihua ^a  

^a HANGZHOU DIANZI UNIVERSITY   (China)

^b ZHEJIANG CANCER HOSPITAL   (China)

Author keywords

3D Convolutional neural network (3D CNN),Deep learning,Data augmentation; Breast cancer classification; Dynamic contrast enhancement magnetic resonance imaging (DCE MRI)

Indexed keywords

CLASSIFICATION (OF INFORMATION); CONVOLUTION; DEEP LEARNING; FEATURE EXTRACTION; HEALTH CARE; IMAGE SEGMENTATION; LEARNING SYSTEMS; MAGNETIC RESONANCE IMAGING; NETWORK ARCHITECTURE; NEURAL NETWORKS; NOISE ABATEMENT; TUMORS;

AREA UNDER THE ROC CURVE; BREAST CANCER CLASSIFICATIONS; BREAST TUMOR CLASSIFICATIONS; CONVOLUTIONAL NEURAL NETWORK; DATA AUGMENTATION; DCE-MRI; DYNAMIC CONTRAST ENHANCED; SPATIAL INFORMATIONS;

MEDICAL IMAGING;

EID: 85020428820     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.2254716     Document Type: Conference Paper

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