Beyond the Patterns 22 - Udaranga Wickramasinghe - Voxel2Mesh: 3D Mesh Models from Volumetric Data

It’s a great pleasure to welcome Udaranga Wickramasinghe from EPFL, Lausanne, Switzerland at our lab for an invited talk! Abstract: CNN-based volumetric methods that label individual voxels dominate the field of biomedical image segmentation. However, 3D surface representations of the segmented structures are often required for tasks like shape analysis. They can be obtained by post-processing the labeled volumes which typically introduces artifacts and prevents end-to-end training. In this talk, I introduce Voxel2Mesh, a novel architecture that goes from 3D image volumes to 3D surfaces directly without any post-processing and with better accuracy than current methods when using smaller training datasets. I will discuss in detail about the motivation, design choices, strengths and limitations of the architecture. I will also discuss how this can help to accelerate the adoption of deep learning techniques for shape analysis in medical imaging. Short Bio: Udaranga Wickramasinghe is a PhD student at CVLAB – EP