16 citations · 20 across the 4 of their papers we have counts for
4 papers
Global Planar Convolutions for improved context aggregation in Brain Tumor Segmentation
Santi Puch, Irina Sánchez, Aura Hernández +2
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…
Few-shot Learning with Deep Triplet Networks for Brain Imaging Modality Recognition
Santi Puch, Irina Sánchez, Matt Rowe
Image modality recognition is essential for efficient imaging workflows in current clinical environments, where multiple imaging modalities are used to better comprehend complex di…
3D Convolutional Neural Networks for Brain Tumor Segmentation: A Comparison of Multi-resolution Architectures
Adrià Casamitjana, Santi Puch, Asier Aduriz +1
This paper analyzes the use of 3D Convolutional Neural Networks for brain tumor segmentation in MR images. We address the problem using three different architectures that combine f…
Voxelwise nonlinear regression toolbox for neuroimage analysis: Application to aging and neurodegenerative disease modeling
Santi Puch, Asier Aduriz, Adrià Casamitjana +8
This paper describes a new neuroimaging analysis toolbox that allows for the modeling of nonlinear effects at the voxel level, overcoming limitations of methods based on linear mod…