TY  - CONF
AU  - Santi Puch
AU  - Irina Sanchez
AU  - Aura Hernandez-Sabate
AU  - Gemma Piella
AU  - Vesna Prckovska
A2  - MICCAIW
PY  - 2018//
TI  - Global Planar Convolutions for Improved Context Aggregation in Brain Tumor Segmentation
T2  - LNCS
BT  - International MICCAI Brainlesion Workshop
SP  - 393
EP  - 405
VL  - 11384
KW  - Brain tumors
KW  - 3D fully-convolutional CNN
KW  - Magnetic resonance imaging
KW  - Global planar convolution
N2  - In this work, we introduce the Global Planar Convolution module as a building-block for fully-convolutional networks that aggregates global information and, therefore, enhances the context perception capabilities of segmentation networks in the context of brain tumor segmentation. We implement two baseline architectures (3D UNet and a residual version of 3D UNet, ResUNet) and present a novel architecture based on these two architectures, ContextNet, that includes the proposed Global Planar Convolution module. We show that the addition of such module eliminates the need of building networks with several representation levels, which tend to be over-parametrized and to showcase slow rates of convergence. Furthermore, we provide a visual demonstration of the behavior of GPC modules via visualization of intermediate representations. We finally participate in the 2018 edition of the BraTS challenge with our best performing models, that are based on ContextNet, and report the evaluation scores on the validation and the test sets of the challenge.
UR  - https://link.springer.com/chapter/10.1007/978-3-030-11726-9_35
L1  - http://refbase.cvc.uab.es/files/PSH2018.pdf
N1  - ADAS; 600.118
ID  - Santi Puch2018
ER  -