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Document type:
Konferenzbeitrag 
Author(s):
Magdalini Paschali; Stefano Gasperini; Abhijit Guha Roy; Michael Y.-S. Fang; Nassir Navab 
Title:
3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation 
Abstract:
Model architectures have been dramatically increasing in size, improving performance at the cost of resource requirements. In this paper we propose 3DQ, a ternary quantization method, applied for the first time to 3D Fully Convolutional Neural Networks, enabling 16x model compression while maintaining performance on par with full precision models. We extensively evaluate 3DQ on two datasets for the challenging task of whole brain segmentation. Additionally, we showcase the ability of our method...    »
 
Keywords:
quantization; 3D segmentation; medical imaging; compression 
Dewey Decimal Classification:
000 Informatik, Wissen, Systeme 
Book / Congress title:
Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 
Year:
2019 
Month:
Oct 
Reviewed:
ja 
Language:
en 
Notes:
The first two authors contributed equally.