no code implementations • 14 Feb 2024 • Miguel Fainstein, Viviana Siless, Emmanuel Iarussi
In recent years, there has been a growing interest in training Neural Networks to approximate Unsigned Distance Fields (UDFs) for representing open surfaces in the context of 3D reconstruction.
no code implementations • 7 Jul 2023 • Paula Feldman, Miguel Fainstein, Viviana Siless, Claudio Delrieux, Emmanuel Iarussi
We present a data-driven generative framework for synthesizing blood vessel 3D geometry.
1 code implementation • 27 Jun 2023 • Duilio Deangeli, Emmanuel Iarussi, Juan Pablo Princich, Mariana Bendersky, Ignacio Larrabide, José Ignacio Orlando
This paper introduces a novel method to learn normal asymmetry patterns in homologous brain structures based on anomaly detection and representation learning.
1 code implementation • 23 Sep 2020 • Emmanuel Iarussi, Felix Thomsen, Claudio Delrieux
Our method allows to generate a virtually infinite number of patches of realistic bone micro-structure, and thereby likely serves for the development of bone-biomarkers and to simulate bone therapies in advance.
no code implementations • 29 Nov 2019 • Pablo Navarro, José Ignacio Orlando, Claudio Delrieux, Emmanuel Iarussi
Finding point-wise correspondences between images is a long-standing problem in image analysis.