How to predict the inside from the outside? Segment, register, model and infer! (Talk)
Observing and modeling the human body has attracted scientific efforts since the very early times in history. In the recent decades, though, several imaging modalities, such as Computed Tomography scanners (CT), Magnetic Resonance Imaging (MRI), or X-ray have provided the means to “see” inside the body. Most interestingly, there is growing evidence pointing that the shape of the surface of the human body is highly correlated with its internal properties, for example, the body composition, the size of the bones, and the amount of muscle and adipose tissue (fat). In this talk I will go over the used methodology to establish the link between the shape of the surface of the body and the internal anatomic structures, based on the classical problems of segmentation, registration, statistical modeling, and inference.
Biography: Sergi Pujades graduated in Applied Mathematics (2005) at the Facultat de Matemàtiques i Estadística (FME) from the Universitat Politècnica de Catalunya (UPC) in Barcelona, Spain, and in Computer Science (2005) at the École Nationale Supérieure d'Informatique et de Mathématiques Appliquées de Grenoble (ENSIMAG). After working as a research engineer at INRIA Grenoble developing algorithms for stereoscopic shooting, he joined the Binocle3D company (2007) where he managed the R&D Software Department (2009 -2011). In 2015 he received his PhD from University Grenoble Alpes for his work on camera models and algorithms for the creation of video content. Between 2016 and 2018 he was a Post-Doctoral Researcher at Max Planck Institute for Intelligent Systems in Tübingen, Germany. Since December 2018 he is an associate professor at University Grenoble Alpes in the Morpheo INRIA Team. Sergi’s research aims at understanding the world through the capture and analysis of heterogeneous data, in order to create applied digital instruments. Examples of heterogeneous data are optical images obtained with visible light cameras, medical images obtained with Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) scanners, and geometry data obtained with depth sensors. Examples of applied digital instruments are tools that allow to segment and identify anatomic structures, to create anatomic digital twins and to predict the 3D shape of the skeleton of a person from only surface observations.
Details
- 28 November 2024 • 10:00 - 11:00
- MPI IS Tuebingen, 3rd floor, Aquarium
- Perceiving Systems
